Plot
EDA Plot for each crop data
linear reg for yield VS EHF 95
Abbotsford weekly
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27837 -6474 -1373 4047 41932
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 247624.160 53497.038 4.629 0.00169 **
## Week_1 -2171.531 3826.707 -0.567 0.58596
## Week_2 -2744.458 2644.290 -1.038 0.32968
## Week_3 3641.847 3466.401 1.051 0.32413
## Week_4 3003.179 6048.615 0.497 0.63289
## Week_5 1178.247 3445.783 0.342 0.74121
## Week_6 -8750.445 4915.786 -1.780 0.11294
## Week_7 4885.760 6409.091 0.762 0.46775
## Week_8 5235.628 4971.863 1.053 0.32308
## Week_9 1747.502 4600.510 0.380 0.71394
## Week_10 -3484.455 4713.238 -0.739 0.48086
## Week_11 -7730.497 6721.097 -1.150 0.28329
## Week_12 -5157.226 4302.043 -1.199 0.26491
## Week_13 3554.688 4929.279 0.721 0.49136
## Week_14 2938.131 10286.955 0.286 0.78243
## Week_15 11179.958 7376.340 1.516 0.16808
## Week_16 1.334 3193.296 0.000 0.99968
## Week_17 -3851.450 4653.844 -0.828 0.43190
## Week_18 4466.951 3566.116 1.253 0.24572
## Week_19 3144.828 2232.205 1.409 0.19654
## Week_20 7169.321 4975.559 1.441 0.18758
## Week_21 -1530.657 4360.146 -0.351 0.73461
## Week_22 -3232.952 2740.419 -1.180 0.27200
## Week_23 -2143.645 4251.514 -0.504 0.62771
## Week_24 5438.291 4307.202 1.263 0.24229
## Week_25 -7676.930 5358.130 -1.433 0.18982
## Week_26 777.006 1478.901 0.525 0.61356
## Week_27 7691.774 4315.853 1.782 0.11257
## Week_28 3580.131 4283.071 0.836 0.42748
## Week_29 -1154.881 3714.927 -0.311 0.76384
## Week_30 2083.311 2774.364 0.751 0.47421
## Week_31 5982.369 12198.921 0.490 0.63702
## Week_32 -5687.078 3614.449 -1.573 0.15427
## Week_33 -8240.645 5629.085 -1.464 0.18137
## Week_34 27195.753 9710.787 2.801 0.02318 *
## Week_35 -8417.524 5877.329 -1.432 0.18998
## Week_36 8261.557 6418.785 1.287 0.23405
## Week_37 -1111.867 10587.008 -0.105 0.91894
## Week_38 -3434.407 6234.828 -0.551 0.59678
## Week_39 -773.375 5236.137 -0.148 0.88623
## Week_40 -6421.768 8470.863 -0.758 0.47013
## Week_41 -8203.312 7828.657 -1.048 0.32533
## Week_42 11641.966 6518.586 1.786 0.11193
## Week_43 -12452.499 8075.365 -1.542 0.16164
## Week_44 2689.081 6051.644 0.444 0.66856
## Week_45 -14715.632 9651.161 -1.525 0.16583
## Week_46 16405.115 9062.185 1.810 0.10784
## Week_47 -4234.774 4100.397 -1.033 0.33192
## Week_48 2209.198 5307.865 0.416 0.68820
## Week_49 6830.131 5089.663 1.342 0.21645
## Week_50 -7680.498 5335.802 -1.439 0.18799
## Week_51 -3394.036 3890.915 -0.872 0.40846
## Week_52 2109.363 6764.758 0.312 0.76315
## Week_53 -2308.067 4283.919 -0.539 0.60471
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 36040 on 8 degrees of freedom
## Multiple R-squared: 0.9491, Adjusted R-squared: 0.6122
## F-statistic: 2.817 on 53 and 8 DF, p-value: 0.06071
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4213 -1125 -84 1147 4983
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 41267.00 7396.44 5.579 0.000523 ***
## Week_1 159.50 529.08 0.301 0.770741
## Week_2 -459.92 365.60 -1.258 0.243872
## Week_3 331.46 479.26 0.692 0.508751
## Week_4 490.41 836.27 0.586 0.573763
## Week_5 -86.59 476.41 -0.182 0.860296
## Week_6 -1051.44 679.65 -1.547 0.160443
## Week_7 165.41 886.11 0.187 0.856567
## Week_8 1309.93 687.40 1.906 0.093157 .
## Week_9 -566.49 636.06 -0.891 0.399123
## Week_10 -55.58 651.65 -0.085 0.934121
## Week_11 -710.73 929.25 -0.765 0.466328
## Week_12 -301.10 594.79 -0.506 0.626357
## Week_13 88.47 681.52 0.130 0.899920
## Week_14 942.56 1422.26 0.663 0.526139
## Week_15 838.48 1019.84 0.822 0.434803
## Week_16 -32.46 441.50 -0.074 0.943191
## Week_17 -828.63 643.43 -1.288 0.233808
## Week_18 392.15 493.05 0.795 0.449360
## Week_19 690.71 308.62 2.238 0.055595 .
## Week_20 718.53 687.91 1.045 0.326784
## Week_21 112.44 602.83 0.187 0.856675
## Week_22 -14.73 378.89 -0.039 0.969941
## Week_23 -736.03 587.81 -1.252 0.245879
## Week_24 221.83 595.51 0.373 0.719193
## Week_25 -305.94 740.81 -0.413 0.690462
## Week_26 -271.02 204.47 -1.325 0.221611
## Week_27 1663.55 596.71 2.788 0.023635 *
## Week_28 -404.66 592.17 -0.683 0.513685
## Week_29 108.40 513.62 0.211 0.838130
## Week_30 388.34 383.58 1.012 0.340983
## Week_31 -464.93 1686.61 -0.276 0.789797
## Week_32 -4.64 499.73 -0.009 0.992819
## Week_33 -1009.16 778.27 -1.297 0.230892
## Week_34 2567.53 1342.60 1.912 0.092195 .
## Week_35 -1308.31 812.59 -1.610 0.146055
## Week_36 1224.31 887.45 1.380 0.205048
## Week_37 -470.14 1463.75 -0.321 0.756299
## Week_38 77.30 862.02 0.090 0.930749
## Week_39 24.27 723.94 0.034 0.974080
## Week_40 -432.06 1171.17 -0.369 0.721764
## Week_41 473.49 1082.38 0.437 0.673353
## Week_42 1507.43 901.25 1.673 0.132946
## Week_43 -210.32 1116.49 -0.188 0.855269
## Week_44 -702.37 836.69 -0.839 0.425586
## Week_45 -764.99 1334.36 -0.573 0.582193
## Week_46 1168.18 1252.93 0.932 0.378430
## Week_47 -548.78 566.92 -0.968 0.361390
## Week_48 768.53 733.86 1.047 0.325590
## Week_49 169.41 703.69 0.241 0.815807
## Week_50 -489.42 737.72 -0.663 0.525710
## Week_51 -770.43 537.95 -1.432 0.189992
## Week_52 234.75 935.29 0.251 0.808147
## Week_53 -289.59 592.29 -0.489 0.638006
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4983 on 8 degrees of freedom
## Multiple R-squared: 0.9163, Adjusted R-squared: 0.3614
## F-statistic: 1.651 on 53 and 8 DF, p-value: 0.231
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5994 -1963 -161 1272 10520
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 100208.28 12862.34 7.791 5.28e-05 ***
## Week_1 70.66 920.06 0.077 0.9407
## Week_2 -280.53 635.77 -0.441 0.6707
## Week_3 1157.06 833.43 1.388 0.2025
## Week_4 -113.07 1454.27 -0.078 0.9399
## Week_5 -179.41 828.47 -0.217 0.8340
## Week_6 -1901.37 1181.91 -1.609 0.1463
## Week_7 878.86 1540.94 0.570 0.5841
## Week_8 1843.94 1195.39 1.543 0.1615
## Week_9 -1332.39 1106.10 -1.205 0.2628
## Week_10 1049.61 1133.21 0.926 0.3814
## Week_11 -2306.89 1615.96 -1.428 0.1913
## Week_12 -948.67 1034.34 -0.917 0.3859
## Week_13 697.73 1185.15 0.589 0.5723
## Week_14 1442.84 2473.30 0.583 0.5757
## Week_15 1522.11 1773.50 0.858 0.4157
## Week_16 789.24 767.77 1.028 0.3340
## Week_17 -1225.56 1118.93 -1.095 0.3053
## Week_18 1141.85 857.40 1.332 0.2196
## Week_19 993.73 536.69 1.852 0.1012
## Week_20 1066.51 1196.28 0.892 0.3987
## Week_21 -839.57 1048.31 -0.801 0.4463
## Week_22 -927.81 658.88 -1.408 0.1967
## Week_23 -1178.51 1022.20 -1.153 0.2822
## Week_24 1360.14 1035.58 1.313 0.2255
## Week_25 -2343.97 1288.26 -1.819 0.1063
## Week_26 269.62 355.57 0.758 0.4700
## Week_27 3366.10 1037.66 3.244 0.0118 *
## Week_28 -224.66 1029.78 -0.218 0.8328
## Week_29 1036.99 893.18 1.161 0.2791
## Week_30 463.16 667.04 0.694 0.5071
## Week_31 3845.57 2933.00 1.311 0.2262
## Week_32 -1285.01 869.03 -1.479 0.1775
## Week_33 -673.49 1353.41 -0.498 0.6321
## Week_34 6794.01 2334.77 2.910 0.0196 *
## Week_35 -2673.52 1413.09 -1.892 0.0951 .
## Week_36 4127.59 1543.27 2.675 0.0282 *
## Week_37 -2474.94 2545.44 -0.972 0.3594
## Week_38 -349.25 1499.05 -0.233 0.8216
## Week_39 -695.63 1258.93 -0.553 0.5957
## Week_40 -3333.10 2036.66 -1.637 0.1404
## Week_41 -613.71 1882.25 -0.326 0.7528
## Week_42 3909.47 1567.27 2.494 0.0373 *
## Week_43 -3417.51 1941.57 -1.760 0.1164
## Week_44 315.47 1455.00 0.217 0.8338
## Week_45 -4087.96 2320.44 -1.762 0.1161
## Week_46 4392.16 2178.83 2.016 0.0786 .
## Week_47 -625.61 985.86 -0.635 0.5434
## Week_48 956.91 1276.17 0.750 0.4748
## Week_49 1533.99 1223.71 1.254 0.2454
## Week_50 -1444.04 1282.89 -1.126 0.2930
## Week_51 -1701.51 935.50 -1.819 0.1064
## Week_52 1976.93 1626.46 1.215 0.2588
## Week_53 -1614.43 1029.99 -1.567 0.1557
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8666 on 8 degrees of freedom
## Multiple R-squared: 0.9698, Adjusted R-squared: 0.7694
## F-statistic: 4.841 on 53 and 8 DF, p-value: 0.01152
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5837.8 -1725.3 -198.2 1208.5 7536.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 123407.92 10478.35 11.777 2.47e-06 ***
## Week_1 806.42 749.53 1.076 0.3133
## Week_2 -46.83 517.93 -0.090 0.9302
## Week_3 899.86 678.96 1.325 0.2216
## Week_4 -1270.65 1184.73 -1.073 0.3148
## Week_5 -69.53 674.92 -0.103 0.9205
## Week_6 86.49 962.84 0.090 0.9306
## Week_7 -317.43 1255.33 -0.253 0.8068
## Week_8 -238.38 973.83 -0.245 0.8128
## Week_9 -164.69 901.09 -0.183 0.8595
## Week_10 202.39 923.17 0.219 0.8320
## Week_11 -500.89 1316.45 -0.380 0.7135
## Week_12 -479.77 842.63 -0.569 0.5847
## Week_13 -292.09 965.49 -0.303 0.7700
## Week_14 2049.21 2014.88 1.017 0.3389
## Week_15 1394.37 1444.79 0.965 0.3628
## Week_16 81.82 625.46 0.131 0.8991
## Week_17 44.46 911.54 0.049 0.9623
## Week_18 -78.92 698.49 -0.113 0.9128
## Week_19 394.91 437.22 0.903 0.3928
## Week_20 535.20 974.55 0.549 0.5979
## Week_21 -553.01 854.01 -0.648 0.5354
## Week_22 -300.79 536.76 -0.560 0.5906
## Week_23 -437.69 832.73 -0.526 0.6134
## Week_24 771.14 843.64 0.914 0.3874
## Week_25 -1660.72 1049.49 -1.582 0.1522
## Week_26 -132.08 289.67 -0.456 0.6605
## Week_27 1726.28 845.34 2.042 0.0754 .
## Week_28 67.73 838.92 0.081 0.9376
## Week_29 495.58 727.63 0.681 0.5150
## Week_30 278.22 543.41 0.512 0.6225
## Week_31 3385.97 2389.38 1.417 0.1942
## Week_32 212.87 707.95 0.301 0.7713
## Week_33 -1152.92 1102.56 -1.046 0.3263
## Week_34 1066.17 1902.03 0.561 0.5905
## Week_35 624.93 1151.18 0.543 0.6020
## Week_36 -2375.88 1257.23 -1.890 0.0955 .
## Week_37 -1847.96 2073.65 -0.891 0.3989
## Week_38 649.91 1221.20 0.532 0.6091
## Week_39 88.93 1025.59 0.087 0.9330
## Week_40 -1053.59 1659.17 -0.635 0.5432
## Week_41 804.23 1533.38 0.524 0.6142
## Week_42 1521.51 1276.78 1.192 0.2675
## Week_43 42.96 1581.70 0.027 0.9790
## Week_44 -1031.52 1185.32 -0.870 0.4095
## Week_45 -2714.56 1890.35 -1.436 0.1889
## Week_46 3581.81 1774.99 2.018 0.0783 .
## Week_47 268.70 803.14 0.335 0.7466
## Week_48 1108.38 1039.64 1.066 0.3175
## Week_49 443.45 996.90 0.445 0.6682
## Week_50 -952.43 1045.11 -0.911 0.3888
## Week_51 -326.53 762.11 -0.428 0.6796
## Week_52 324.71 1325.00 0.245 0.8126
## Week_53 -68.02 839.08 -0.081 0.9374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7060 on 8 degrees of freedom
## Multiple R-squared: 0.9275, Adjusted R-squared: 0.4472
## F-statistic: 1.931 on 53 and 8 DF, p-value: 0.1623
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3765.4 -913.4 -359.8 954.4 4594.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 36184.14 6340.82 5.707 0.000451 ***
## Week_1 421.32 453.57 0.929 0.380112
## Week_2 -406.31 313.42 -1.296 0.230984
## Week_3 549.88 410.86 1.338 0.217566
## Week_4 89.98 716.92 0.126 0.903221
## Week_5 -56.65 408.42 -0.139 0.893107
## Week_6 -1020.79 582.65 -1.752 0.117878
## Week_7 -230.95 759.65 -0.304 0.768870
## Week_8 1753.05 589.30 2.975 0.017740 *
## Week_9 -853.03 545.28 -1.564 0.156359
## Week_10 127.30 558.64 0.228 0.825462
## Week_11 -1291.86 796.63 -1.622 0.143535
## Week_12 -263.73 509.91 -0.517 0.618997
## Week_13 251.56 584.25 0.431 0.678142
## Week_14 1259.70 1219.28 1.033 0.331753
## Week_15 477.74 874.29 0.546 0.599675
## Week_16 -45.16 378.49 -0.119 0.907962
## Week_17 -935.08 551.60 -1.695 0.128482
## Week_18 539.98 422.68 1.278 0.237243
## Week_19 531.49 264.58 2.009 0.079419 .
## Week_20 759.79 589.74 1.288 0.233632
## Week_21 -44.56 516.79 -0.086 0.933410
## Week_22 -95.45 324.81 -0.294 0.776346
## Week_23 -660.23 503.92 -1.310 0.226494
## Week_24 94.10 510.52 0.184 0.858345
## Week_25 -237.42 635.08 -0.374 0.718232
## Week_26 -186.85 175.29 -1.066 0.317553
## Week_27 1762.13 511.54 3.445 0.008762 **
## Week_28 -681.49 507.66 -1.342 0.216306
## Week_29 -174.30 440.32 -0.396 0.702555
## Week_30 302.91 328.84 0.921 0.383902
## Week_31 918.94 1445.90 0.636 0.542818
## Week_32 -66.10 428.41 -0.154 0.881195
## Week_33 -718.92 667.20 -1.078 0.312663
## Week_34 2947.85 1150.99 2.561 0.033587 *
## Week_35 -1253.79 696.62 -1.800 0.109583
## Week_36 1010.79 760.80 1.329 0.220628
## Week_37 -676.69 1254.84 -0.539 0.604384
## Week_38 86.66 738.99 0.117 0.909536
## Week_39 125.72 620.62 0.203 0.844523
## Week_40 -1368.57 1004.02 -1.363 0.209980
## Week_41 722.08 927.90 0.778 0.458852
## Week_42 1921.01 772.63 2.486 0.037737 *
## Week_43 -572.65 957.14 -0.598 0.566194
## Week_44 -751.93 717.28 -1.048 0.325130
## Week_45 -841.69 1143.92 -0.736 0.482867
## Week_46 1151.20 1074.11 1.072 0.315088
## Week_47 -462.00 486.01 -0.951 0.369636
## Week_48 592.93 629.12 0.942 0.373537
## Week_49 263.89 603.26 0.437 0.673364
## Week_50 -398.73 632.43 -0.630 0.545969
## Week_51 -874.17 461.18 -1.896 0.094619 .
## Week_52 585.33 801.80 0.730 0.486204
## Week_53 -435.37 507.76 -0.857 0.416150
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4272 on 8 degrees of freedom
## Multiple R-squared: 0.9421, Adjusted R-squared: 0.5586
## F-statistic: 2.456 on 53 and 8 DF, p-value: 0.08845
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3404.7 -1029.7 -210.9 722.1 4629.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23961.701 6607.473 3.626 0.00672 **
## Week_1 -702.709 472.641 -1.487 0.17539
## Week_2 157.816 326.599 0.483 0.64189
## Week_3 -292.068 428.139 -0.682 0.51439
## Week_4 1208.512 747.071 1.618 0.14440
## Week_5 -1049.263 425.592 -2.465 0.03899 *
## Week_6 -630.246 607.154 -1.038 0.32961
## Week_7 751.474 791.593 0.949 0.37025
## Week_8 1135.322 614.080 1.849 0.10166
## Week_9 -500.700 568.214 -0.881 0.40392
## Week_10 -701.512 582.137 -1.205 0.26261
## Week_11 -1225.466 830.130 -1.476 0.17812
## Week_12 -449.506 531.350 -0.846 0.42215
## Week_13 933.924 608.820 1.534 0.16358
## Week_14 -633.648 1270.552 -0.499 0.63140
## Week_15 1312.632 911.059 1.441 0.18762
## Week_16 652.696 394.407 1.655 0.13654
## Week_17 -634.967 574.801 -1.105 0.30142
## Week_18 -487.901 440.455 -1.108 0.30017
## Week_19 232.146 275.702 0.842 0.42423
## Week_20 1266.244 614.536 2.060 0.07330 .
## Week_21 -303.061 538.526 -0.563 0.58902
## Week_22 -1094.305 338.472 -3.233 0.01200 *
## Week_23 661.858 525.109 1.260 0.24304
## Week_24 57.603 531.987 0.108 0.91644
## Week_25 -4.102 661.788 -0.006 0.99521
## Week_26 -61.315 182.661 -0.336 0.74575
## Week_27 463.250 533.055 0.869 0.41014
## Week_28 772.263 529.007 1.460 0.18246
## Week_29 -846.214 458.834 -1.844 0.10237
## Week_30 -29.721 342.664 -0.087 0.93301
## Week_31 1311.893 1506.701 0.871 0.40928
## Week_32 -88.776 446.424 -0.199 0.84733
## Week_33 -1191.185 695.254 -1.713 0.12501
## Week_34 1181.500 1199.389 0.985 0.35343
## Week_35 366.011 725.915 0.504 0.62771
## Week_36 -315.120 792.791 -0.397 0.70141
## Week_37 915.710 1307.612 0.700 0.50360
## Week_38 -1073.071 770.070 -1.393 0.20097
## Week_39 -931.650 646.721 -1.441 0.18767
## Week_40 377.127 1046.245 0.360 0.72784
## Week_41 -810.362 966.925 -0.838 0.42631
## Week_42 528.123 805.117 0.656 0.53026
## Week_43 -1214.846 997.397 -1.218 0.25792
## Week_44 1381.988 747.445 1.849 0.10164
## Week_45 -1594.716 1192.025 -1.338 0.21774
## Week_46 1576.992 1119.280 1.409 0.19652
## Week_47 438.031 506.444 0.865 0.41227
## Week_48 -479.170 655.580 -0.731 0.48569
## Week_49 99.753 628.629 0.159 0.87785
## Week_50 -512.787 659.030 -0.778 0.45891
## Week_51 9.542 480.571 0.020 0.98464
## Week_52 -301.734 835.522 -0.361 0.72735
## Week_53 -197.042 529.111 -0.372 0.71927
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4452 on 8 degrees of freedom
## Multiple R-squared: 0.9341, Adjusted R-squared: 0.4972
## F-statistic: 2.138 on 53 and 8 DF, p-value: 0.1266
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10582.2 -2734.3 -964.6 2582.2 12444.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86931.8 19493.7 4.459 0.00211 **
## Week_1 622.7 1394.4 0.447 0.66705
## Week_2 -813.6 963.6 -0.844 0.42301
## Week_3 -1019.3 1263.1 -0.807 0.44301
## Week_4 1161.6 2204.0 0.527 0.61246
## Week_5 974.9 1255.6 0.776 0.45985
## Week_6 -3132.8 1791.3 -1.749 0.11842
## Week_7 2375.3 2335.4 1.017 0.33888
## Week_8 1280.3 1811.7 0.707 0.49982
## Week_9 -1105.3 1676.4 -0.659 0.52820
## Week_10 -830.9 1717.5 -0.484 0.64148
## Week_11 -555.4 2449.1 -0.227 0.82630
## Week_12 -127.8 1567.6 -0.082 0.93701
## Week_13 -593.5 1796.2 -0.330 0.74957
## Week_14 511.5 3748.5 0.136 0.89483
## Week_15 3093.1 2687.9 1.151 0.28306
## Week_16 1995.0 1163.6 1.715 0.12477
## Week_17 -2041.0 1695.8 -1.204 0.26317
## Week_18 845.6 1299.5 0.651 0.53344
## Week_19 1770.3 813.4 2.176 0.06120 .
## Week_20 1772.9 1813.0 0.978 0.35679
## Week_21 948.4 1588.8 0.597 0.56708
## Week_22 -988.1 998.6 -0.989 0.35141
## Week_23 -3053.1 1549.2 -1.971 0.08425 .
## Week_24 1165.0 1569.5 0.742 0.47915
## Week_25 -1809.0 1952.4 -0.927 0.38128
## Week_26 -495.9 538.9 -0.920 0.38437
## Week_27 3532.2 1572.6 2.246 0.05490 .
## Week_28 912.1 1560.7 0.584 0.57503
## Week_29 2202.8 1353.7 1.627 0.14232
## Week_30 447.8 1010.9 0.443 0.66954
## Week_31 -4140.4 4445.2 -0.931 0.37888
## Week_32 103.0 1317.1 0.078 0.93961
## Week_33 -4513.0 2051.2 -2.200 0.05898 .
## Week_34 4737.9 3538.5 1.339 0.21738
## Week_35 -1711.8 2141.6 -0.799 0.44720
## Week_36 4970.6 2338.9 2.125 0.06629 .
## Week_37 -1614.6 3857.8 -0.419 0.68658
## Week_38 178.6 2271.9 0.079 0.93928
## Week_39 -1377.1 1908.0 -0.722 0.49099
## Week_40 -2170.8 3086.7 -0.703 0.50183
## Week_41 841.9 2852.7 0.295 0.77541
## Week_42 4085.1 2375.3 1.720 0.12377
## Week_43 -2221.6 2942.6 -0.755 0.47189
## Week_44 150.5 2205.2 0.068 0.94728
## Week_45 -3618.9 3516.8 -1.029 0.33357
## Week_46 4366.6 3302.2 1.322 0.22261
## Week_47 -1076.3 1494.1 -0.720 0.49184
## Week_48 3038.5 1934.1 1.571 0.15482
## Week_49 538.8 1854.6 0.291 0.77881
## Week_50 -2114.1 1944.3 -1.087 0.30856
## Week_51 -1203.2 1417.8 -0.849 0.42073
## Week_52 1993.5 2465.0 0.809 0.44207
## Week_53 -3387.0 1561.0 -2.170 0.06184 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13130 on 8 degrees of freedom
## Multiple R-squared: 0.9163, Adjusted R-squared: 0.3619
## F-statistic: 1.653 on 53 and 8 DF, p-value: 0.2305
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7425.1 -1830.7 159.5 1640.6 10838.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 38575.24 13283.48 2.904 0.0198 *
## Week_1 -1403.29 950.18 -1.477 0.1780
## Week_2 -75.63 656.59 -0.115 0.9111
## Week_3 -1129.77 860.72 -1.313 0.2257
## Week_4 2132.49 1501.89 1.420 0.1934
## Week_5 -116.15 855.60 -0.136 0.8954
## Week_6 -1094.49 1220.61 -0.897 0.3961
## Week_7 2670.75 1591.40 1.678 0.1318
## Week_8 -1066.28 1234.53 -0.864 0.4129
## Week_9 1750.92 1142.32 1.533 0.1639
## Week_10 -2646.91 1170.31 -2.262 0.0536 .
## Week_11 2260.02 1668.87 1.354 0.2127
## Week_12 -2260.07 1068.21 -2.116 0.0673 .
## Week_13 1660.71 1223.96 1.357 0.2119
## Week_14 -3561.38 2554.28 -1.394 0.2007
## Week_15 2932.58 1831.57 1.601 0.1480
## Week_16 -81.53 792.91 -0.103 0.9206
## Week_17 1751.79 1155.56 1.516 0.1680
## Week_18 -435.27 885.48 -0.492 0.6362
## Week_19 358.92 554.26 0.648 0.5354
## Week_20 957.48 1235.45 0.775 0.4606
## Week_21 479.84 1082.64 0.443 0.6693
## Week_22 191.51 680.45 0.281 0.7855
## Week_23 270.30 1055.66 0.256 0.8044
## Week_24 957.57 1069.49 0.895 0.3967
## Week_25 -827.69 1330.44 -0.622 0.5512
## Week_26 87.36 367.22 0.238 0.8179
## Week_27 -1019.80 1071.64 -0.952 0.3692
## Week_28 1946.71 1063.50 1.830 0.1046
## Week_29 -162.84 922.43 -0.177 0.8643
## Week_30 244.00 688.88 0.354 0.7323
## Week_31 -5340.99 3029.03 -1.763 0.1159
## Week_32 -1520.77 897.48 -1.694 0.1286
## Week_33 -1147.44 1397.72 -0.821 0.4355
## Week_34 3479.24 2411.22 1.443 0.1870
## Week_35 -3175.18 1459.36 -2.176 0.0613 .
## Week_36 3175.92 1593.80 1.993 0.0814 .
## Week_37 2750.35 2628.79 1.046 0.3260
## Week_38 -2153.98 1548.13 -1.391 0.2016
## Week_39 -373.91 1300.15 -0.288 0.7810
## Week_40 1410.62 2103.34 0.671 0.5213
## Week_41 -1818.99 1943.88 -0.936 0.3768
## Week_42 -1358.87 1618.59 -0.840 0.4255
## Week_43 339.94 2005.14 0.170 0.8696
## Week_44 2361.83 1502.64 1.572 0.1546
## Week_45 -844.36 2396.41 -0.352 0.7337
## Week_46 1400.81 2250.17 0.623 0.5509
## Week_47 -434.00 1018.14 -0.426 0.6812
## Week_48 -826.90 1317.96 -0.627 0.5479
## Week_49 179.49 1263.78 0.142 0.8906
## Week_50 -818.68 1324.90 -0.618 0.5538
## Week_51 523.05 966.13 0.541 0.6030
## Week_52 -1834.04 1679.71 -1.092 0.3067
## Week_53 -330.80 1063.71 -0.311 0.7638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8950 on 8 degrees of freedom
## Multiple R-squared: 0.885, Adjusted R-squared: 0.1231
## F-statistic: 1.162 on 53 and 8 DF, p-value: 0.4452
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9574.4 -2626.2 -828.6 2319.2 12062.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 96214.07 18287.79 5.261 0.000763 ***
## Week_1 864.57 1308.15 0.661 0.527240
## Week_2 -647.67 903.94 -0.716 0.494067
## Week_3 1316.81 1184.98 1.111 0.298740
## Week_4 -216.05 2067.70 -0.104 0.919354
## Week_5 -50.65 1177.93 -0.043 0.966754
## Week_6 -2597.43 1680.45 -1.546 0.160764
## Week_7 1128.01 2190.93 0.515 0.620575
## Week_8 1744.02 1699.62 1.026 0.334855
## Week_9 -1174.94 1572.67 -0.747 0.476387
## Week_10 19.93 1611.20 0.012 0.990432
## Week_11 -3106.88 2297.59 -1.352 0.213281
## Week_12 -749.85 1470.64 -0.510 0.623899
## Week_13 966.28 1685.06 0.573 0.582104
## Week_14 1617.57 3516.56 0.460 0.657769
## Week_15 2003.33 2521.58 0.794 0.449843
## Week_16 1978.71 1091.62 1.813 0.107456
## Week_17 -2610.72 1590.90 -1.641 0.139419
## Week_18 1201.27 1219.06 0.985 0.353288
## Week_19 2049.35 763.07 2.686 0.027682 *
## Week_20 1696.67 1700.88 0.998 0.347722
## Week_21 -414.95 1490.50 -0.278 0.787770
## Week_22 -642.76 936.80 -0.686 0.512030
## Week_23 -2279.89 1453.37 -1.569 0.155357
## Week_24 964.27 1472.40 0.655 0.530909
## Week_25 -2834.51 1831.66 -1.548 0.160329
## Week_26 -253.21 505.56 -0.501 0.629964
## Week_27 4813.40 1475.36 3.263 0.011484 *
## Week_28 465.76 1464.15 0.318 0.758547
## Week_29 947.86 1269.94 0.746 0.476794
## Week_30 276.49 948.41 0.292 0.778061
## Week_31 4293.72 4170.16 1.030 0.333305
## Week_32 -20.41 1235.59 -0.017 0.987228
## Week_33 -3697.88 1924.28 -1.922 0.090878 .
## Week_34 7274.26 3319.60 2.191 0.059799 .
## Week_35 -690.19 2009.15 -0.344 0.740057
## Week_36 2965.91 2194.24 1.352 0.213451
## Week_37 -5179.06 3619.13 -1.431 0.190304
## Week_38 186.13 2131.36 0.087 0.932556
## Week_39 -1639.98 1789.96 -0.916 0.386342
## Week_40 -2550.36 2895.74 -0.881 0.404146
## Week_41 2136.35 2676.20 0.798 0.447757
## Week_42 5077.45 2228.36 2.279 0.052188 .
## Week_43 -2317.80 2760.54 -0.840 0.425501
## Week_44 -549.43 2068.73 -0.266 0.797272
## Week_45 -7212.95 3299.22 -2.186 0.060271 .
## Week_46 7210.22 3097.88 2.327 0.048352 *
## Week_47 -70.61 1401.71 -0.050 0.961059
## Week_48 3032.03 1814.48 1.671 0.133262
## Week_49 1772.54 1739.88 1.019 0.338130
## Week_50 -3077.15 1824.03 -1.687 0.130084
## Week_51 -1938.64 1330.10 -1.458 0.183080
## Week_52 2267.84 2312.51 0.981 0.355471
## Week_53 -2077.35 1464.44 -1.419 0.193798
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12320 on 8 degrees of freedom
## Multiple R-squared: 0.9484, Adjusted R-squared: 0.6068
## F-statistic: 2.776 on 53 and 8 DF, p-value: 0.06325
Kelowna weekly
## [1] "NA value found at row 17 and column 47"
## [1] "NA value found at row 17 and column 48"
## [1] "NA value found at row 17 and column 49"
## [1] "NA value found at row 57 and column 55"
## [1] "There are 4 NA in the matrix X in Kelowna station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -30154.8 -6135.8 712.3 7224.2 26419.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 254454.9 70907.1 3.589 0.01152 *
## Week_1 9439.3 3995.8 2.362 0.05611 .
## Week_2 -3840.2 2552.3 -1.505 0.18313
## Week_3 -4066.3 4223.3 -0.963 0.37281
## Week_4 6566.7 3577.6 1.836 0.11610
## Week_5 -6977.7 3332.6 -2.094 0.08117 .
## Week_6 2346.9 2280.3 1.029 0.34306
## Week_7 -4405.8 2991.0 -1.473 0.19118
## Week_8 6088.8 3069.5 1.984 0.09455 .
## Week_9 -2005.2 4852.3 -0.413 0.69379
## Week_10 -197.9 3949.4 -0.050 0.96166
## Week_11 -5271.4 3296.5 -1.599 0.16092
## Week_12 -314.6 3867.2 -0.081 0.93780
## Week_13 2065.0 5988.0 0.345 0.74197
## Week_14 6474.1 5175.1 1.251 0.25749
## Week_15 15634.6 4786.3 3.267 0.01711 *
## Week_16 -1074.1 4244.7 -0.253 0.80867
## Week_17 -24290.2 4655.2 -5.218 0.00198 **
## Week_18 2128.1 3328.9 0.639 0.54626
## Week_19 5076.9 3173.8 1.600 0.16080
## Week_20 1830.8 2936.3 0.624 0.55590
## Week_21 5182.3 3423.1 1.514 0.18082
## Week_22 -12541.4 3919.7 -3.200 0.01861 *
## Week_23 -1653.5 3275.6 -0.505 0.63171
## Week_24 9563.5 3834.2 2.494 0.04689 *
## Week_25 -8258.8 3408.0 -2.423 0.05162 .
## Week_26 2224.8 1214.6 1.832 0.11670
## Week_27 1278.9 5758.2 0.222 0.83160
## Week_28 5099.3 6685.0 0.763 0.47449
## Week_29 -308.1 8341.8 -0.037 0.97174
## Week_30 -1188.9 6547.5 -0.182 0.86189
## Week_31 1457.7 5650.9 0.258 0.80506
## Week_32 -2317.8 9721.5 -0.238 0.81949
## Week_33 17332.7 7236.2 2.395 0.05364 .
## Week_34 6067.5 11218.0 0.541 0.60807
## Week_35 7128.2 6922.9 1.030 0.34288
## Week_36 -34922.4 6136.6 -5.691 0.00127 **
## Week_37 9970.6 5411.6 1.842 0.11499
## Week_38 1583.9 5484.0 0.289 0.78244
## Week_39 1229.5 5659.8 0.217 0.83523
## Week_40 3828.9 6468.2 0.592 0.57549
## Week_41 -13650.5 6388.0 -2.137 0.07648 .
## Week_42 3479.1 7900.1 0.440 0.67508
## Week_43 5254.8 8613.5 0.610 0.56419
## Week_44 2164.5 3729.6 0.580 0.58279
## Week_45 2399.5 6028.6 0.398 0.70439
## Week_46 -4232.3 4628.8 -0.914 0.39580
## Week_47 5739.4 4220.4 1.360 0.22273
## Week_48 2652.9 3446.3 0.770 0.47065
## Week_49 -5711.5 3232.3 -1.767 0.12765
## Week_50 2010.6 5630.5 0.357 0.73325
## Week_51 4146.0 3824.5 1.084 0.31996
## Week_52 1642.3 3186.3 0.515 0.62468
## Week_53 -1057.9 2569.2 -0.412 0.69481
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 35570 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9606, Adjusted R-squared: 0.6121
## F-statistic: 2.757 on 53 and 6 DF, p-value: 0.1008
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4248 -1103 18 1152 3842
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 33590.31 10323.46 3.254 0.01738 *
## Week_1 1054.09 581.76 1.812 0.11996
## Week_2 -664.55 371.59 -1.788 0.12393
## Week_3 -277.34 614.87 -0.451 0.66779
## Week_4 586.74 520.87 1.126 0.30300
## Week_5 -715.63 485.20 -1.475 0.19068
## Week_6 369.49 331.98 1.113 0.30831
## Week_7 -702.58 435.47 -1.613 0.15779
## Week_8 913.15 446.89 2.043 0.08704 .
## Week_9 -553.82 706.46 -0.784 0.46289
## Week_10 198.69 575.00 0.346 0.74148
## Week_11 -675.12 479.94 -1.407 0.20915
## Week_12 594.93 563.03 1.057 0.33134
## Week_13 -550.34 871.79 -0.631 0.55114
## Week_14 1322.64 753.44 1.755 0.12971
## Week_15 1404.07 696.85 2.015 0.09054 .
## Week_16 -50.45 617.99 -0.082 0.93759
## Week_17 -2469.89 677.76 -3.644 0.01078 *
## Week_18 138.19 484.65 0.285 0.78513
## Week_19 588.05 462.08 1.273 0.25024
## Week_20 143.15 427.50 0.335 0.74913
## Week_21 553.64 498.37 1.111 0.30914
## Week_22 -1078.15 570.67 -1.889 0.10776
## Week_23 94.57 476.90 0.198 0.84936
## Week_24 422.13 558.22 0.756 0.47816
## Week_25 -389.16 496.17 -0.784 0.46268
## Week_26 160.19 176.83 0.906 0.39991
## Week_27 140.03 838.34 0.167 0.87283
## Week_28 -198.91 973.28 -0.204 0.84482
## Week_29 408.55 1214.49 0.336 0.74802
## Week_30 -318.03 953.26 -0.334 0.75001
## Week_31 -392.14 822.73 -0.477 0.65049
## Week_32 724.27 1415.37 0.512 0.62713
## Week_33 1425.23 1053.53 1.353 0.22487
## Week_34 768.77 1633.24 0.471 0.65448
## Week_35 474.34 1007.91 0.471 0.65453
## Week_36 -3318.04 893.44 -3.714 0.00992 **
## Week_37 940.77 787.88 1.194 0.27752
## Week_38 593.36 798.42 0.743 0.48546
## Week_39 798.80 824.02 0.969 0.36979
## Week_40 762.89 941.72 0.810 0.44881
## Week_41 -1889.89 930.04 -2.032 0.08841 .
## Week_42 -65.53 1150.18 -0.057 0.95641
## Week_43 47.78 1254.05 0.038 0.97084
## Week_44 461.84 543.00 0.851 0.42766
## Week_45 -261.94 877.71 -0.298 0.77543
## Week_46 -375.77 673.92 -0.558 0.59730
## Week_47 219.60 614.45 0.357 0.73304
## Week_48 -28.28 501.76 -0.056 0.95689
## Week_49 -530.60 470.60 -1.128 0.30259
## Week_50 464.74 819.75 0.567 0.59133
## Week_51 348.08 556.81 0.625 0.55490
## Week_52 324.56 463.90 0.700 0.51036
## Week_53 -280.66 374.06 -0.750 0.48145
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5178 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9289, Adjusted R-squared: 0.3007
## F-statistic: 1.479 on 53 and 6 DF, p-value: 0.3307
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14723.5 -3382.8 229.2 4196.2 13326.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 105692.57 31850.27 3.318 0.0160 *
## Week_1 2125.89 1794.85 1.184 0.2810
## Week_2 -1713.57 1146.45 -1.495 0.1856
## Week_3 527.42 1897.01 0.278 0.7903
## Week_4 885.51 1607.00 0.551 0.6015
## Week_5 -1191.23 1496.94 -0.796 0.4565
## Week_6 388.69 1024.25 0.379 0.7174
## Week_7 -858.96 1343.53 -0.639 0.5462
## Week_8 1620.62 1378.77 1.175 0.2844
## Week_9 -1896.36 2179.59 -0.870 0.4177
## Week_10 1186.41 1774.00 0.669 0.5285
## Week_11 -1862.62 1480.74 -1.258 0.2552
## Week_12 1480.00 1737.07 0.852 0.4269
## Week_13 -2149.96 2689.69 -0.799 0.4546
## Week_14 3958.42 2324.55 1.703 0.1395
## Week_15 1740.71 2149.94 0.810 0.4490
## Week_16 1125.31 1906.64 0.590 0.5766
## Week_17 -4571.97 2091.04 -2.186 0.0714 .
## Week_18 -526.76 1495.27 -0.352 0.7367
## Week_19 1760.62 1425.62 1.235 0.2630
## Week_20 814.17 1318.93 0.617 0.5597
## Week_21 1208.20 1537.60 0.786 0.4619
## Week_22 -3277.87 1760.65 -1.862 0.1120
## Week_23 387.68 1471.34 0.263 0.8010
## Week_24 1790.94 1722.25 1.040 0.3385
## Week_25 -2411.54 1530.79 -1.575 0.1662
## Week_26 1273.79 545.56 2.335 0.0583 .
## Week_27 -817.11 2586.47 -0.316 0.7628
## Week_28 58.59 3002.79 0.020 0.9851
## Week_29 2220.45 3746.98 0.593 0.5751
## Week_30 -1671.65 2941.03 -0.568 0.5904
## Week_31 658.52 2538.31 0.259 0.8040
## Week_32 1744.70 4366.73 0.400 0.7033
## Week_33 2876.75 3250.40 0.885 0.4102
## Week_34 4771.24 5038.91 0.947 0.3803
## Week_35 1581.16 3109.63 0.508 0.6293
## Week_36 -7086.68 2756.46 -2.571 0.0423 *
## Week_37 1988.60 2430.80 0.818 0.4446
## Week_38 -107.79 2463.32 -0.044 0.9665
## Week_39 981.25 2542.31 0.386 0.7128
## Week_40 853.83 2905.41 0.294 0.7788
## Week_41 -3789.38 2869.38 -1.321 0.2348
## Week_42 331.13 3548.57 0.093 0.9287
## Week_43 -598.94 3869.04 -0.155 0.8821
## Week_44 1464.76 1675.28 0.874 0.4156
## Week_45 -1264.21 2707.93 -0.467 0.6571
## Week_46 -960.49 2079.20 -0.462 0.6604
## Week_47 -120.36 1895.73 -0.063 0.9514
## Week_48 82.81 1548.04 0.053 0.9591
## Week_49 -633.68 1451.90 -0.436 0.6778
## Week_50 2907.58 2529.13 1.150 0.2940
## Week_51 -510.12 1717.89 -0.297 0.7765
## Week_52 1543.22 1431.23 1.078 0.3224
## Week_53 -770.75 1154.06 -0.668 0.5291
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15980 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9185, Adjusted R-squared: 0.1982
## F-statistic: 1.275 on 53 and 6 DF, p-value: 0.4139
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6787 -2096 146 1982 12627
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 120001.02 20945.20 5.729 0.00123 **
## Week_1 1001.52 1180.32 0.849 0.42870
## Week_2 85.80 753.92 0.114 0.91310
## Week_3 -1457.72 1247.50 -1.169 0.28692
## Week_4 1821.07 1056.79 1.723 0.13562
## Week_5 -1664.96 984.41 -1.691 0.14173
## Week_6 84.04 673.56 0.125 0.90479
## Week_7 -421.76 883.52 -0.477 0.65000
## Week_8 973.76 906.70 1.074 0.32412
## Week_9 -161.96 1433.33 -0.113 0.91372
## Week_10 -288.02 1166.61 -0.247 0.81323
## Week_11 -638.92 973.76 -0.656 0.53607
## Week_12 8.31 1142.32 0.007 0.99443
## Week_13 527.75 1768.78 0.298 0.77548
## Week_14 530.75 1528.66 0.347 0.74029
## Week_15 2076.98 1413.83 1.469 0.19221
## Week_16 -548.24 1253.83 -0.437 0.67723
## Week_17 -3229.28 1375.10 -2.348 0.05718 .
## Week_18 441.39 983.31 0.449 0.66928
## Week_19 -197.83 937.51 -0.211 0.83986
## Week_20 307.69 867.35 0.355 0.73491
## Week_21 888.25 1011.15 0.878 0.41348
## Week_22 -1571.37 1157.83 -1.357 0.22356
## Week_23 -713.96 967.58 -0.738 0.48843
## Week_24 466.58 1132.57 0.412 0.69468
## Week_25 494.08 1006.67 0.491 0.64099
## Week_26 -399.71 358.77 -1.114 0.30786
## Week_27 1399.70 1700.90 0.823 0.44202
## Week_28 536.30 1974.68 0.272 0.79504
## Week_29 717.21 2464.07 0.291 0.78080
## Week_30 448.10 1934.06 0.232 0.82448
## Week_31 -1275.62 1669.23 -0.764 0.47372
## Week_32 2028.87 2871.63 0.707 0.50636
## Week_33 1298.57 2137.51 0.608 0.56578
## Week_34 -2967.45 3313.66 -0.896 0.40500
## Week_35 2001.87 2044.94 0.979 0.36542
## Week_36 -5875.36 1812.69 -3.241 0.01766 *
## Week_37 2532.70 1598.53 1.584 0.16420
## Week_38 -139.24 1619.92 -0.086 0.93430
## Week_39 903.11 1671.86 0.540 0.60852
## Week_40 822.39 1910.64 0.430 0.68192
## Week_41 -892.41 1886.95 -0.473 0.65297
## Week_42 675.40 2333.59 0.289 0.78200
## Week_43 2540.30 2544.34 0.998 0.35663
## Week_44 -522.64 1101.69 -0.474 0.65198
## Week_45 366.61 1780.77 0.206 0.84370
## Week_46 681.99 1367.31 0.499 0.63569
## Week_47 527.08 1246.66 0.423 0.68718
## Week_48 1045.80 1018.01 1.027 0.34390
## Week_49 -1266.77 954.79 -1.327 0.23285
## Week_50 241.37 1663.19 0.145 0.88937
## Week_51 830.84 1129.71 0.735 0.48981
## Week_52 -582.00 941.20 -0.618 0.55906
## Week_53 473.67 758.93 0.624 0.55551
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10510 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.8785, Adjusted R-squared: -0.1946
## F-statistic: 0.8187 on 53 and 6 DF, p-value: 0.6899
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4257.5 -909.1 62.1 1143.0 4236.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 29967.882 10530.540 2.846 0.0293 *
## Week_1 810.150 593.426 1.365 0.2212
## Week_2 -652.709 379.046 -1.722 0.1359
## Week_3 131.664 627.203 0.210 0.8407
## Week_4 193.406 531.316 0.364 0.7283
## Week_5 -450.415 494.929 -0.910 0.3979
## Week_6 256.779 338.644 0.758 0.4770
## Week_7 -664.789 444.206 -1.497 0.1851
## Week_8 830.048 455.858 1.821 0.1185
## Week_9 -403.779 720.629 -0.560 0.5956
## Week_10 159.243 586.531 0.271 0.7951
## Week_11 -714.886 489.572 -1.460 0.1945
## Week_12 505.785 574.321 0.881 0.4124
## Week_13 -373.711 889.282 -0.420 0.6889
## Week_14 1195.488 768.557 1.555 0.1708
## Week_15 390.651 710.826 0.550 0.6025
## Week_16 696.135 630.385 1.104 0.3118
## Week_17 -2186.647 691.354 -3.163 0.0195 *
## Week_18 138.100 494.376 0.279 0.7894
## Week_19 704.842 471.349 1.495 0.1854
## Week_20 169.868 436.073 0.390 0.7103
## Week_21 525.853 508.371 1.034 0.3408
## Week_22 -838.146 582.118 -1.440 0.2000
## Week_23 -210.753 486.465 -0.433 0.6800
## Week_24 533.804 569.420 0.937 0.3847
## Week_25 -462.799 506.121 -0.914 0.3958
## Week_26 288.195 180.377 1.598 0.1612
## Week_27 -413.028 855.157 -0.483 0.6462
## Week_28 129.790 992.801 0.131 0.9003
## Week_29 55.489 1238.850 0.045 0.9657
## Week_30 -425.918 972.382 -0.438 0.6767
## Week_31 86.052 839.231 0.103 0.9217
## Week_32 1269.551 1443.757 0.879 0.4130
## Week_33 773.410 1074.667 0.720 0.4988
## Week_34 1592.584 1665.997 0.956 0.3760
## Week_35 -2.384 1028.127 -0.002 0.9982
## Week_36 -2857.637 911.358 -3.136 0.0202 *
## Week_37 684.519 803.686 0.852 0.4270
## Week_38 563.159 814.440 0.691 0.5151
## Week_39 480.921 840.554 0.572 0.5880
## Week_40 469.918 960.605 0.489 0.6421
## Week_41 -1648.595 948.694 -1.738 0.1329
## Week_42 1095.947 1173.252 0.934 0.3863
## Week_43 -744.176 1279.207 -0.582 0.5819
## Week_44 450.345 553.891 0.813 0.4472
## Week_45 -261.521 895.313 -0.292 0.7800
## Week_46 30.213 687.438 0.044 0.9664
## Week_47 164.912 626.777 0.263 0.8013
## Week_48 -232.763 511.822 -0.455 0.6653
## Week_49 -519.140 480.037 -1.081 0.3210
## Week_50 525.198 836.196 0.628 0.5531
## Week_51 333.531 567.981 0.587 0.5785
## Week_52 197.264 473.202 0.417 0.6913
## Week_53 -308.792 381.563 -0.809 0.4492
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5282 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9297, Adjusted R-squared: 0.3085
## F-statistic: 1.497 on 53 and 6 DF, p-value: 0.3244
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3528.5 -943.8 -85.9 1063.8 3455.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60077.04 9333.07 6.437 0.000665 ***
## Week_1 15.02 525.94 0.029 0.978149
## Week_2 -354.00 335.94 -1.054 0.332572
## Week_3 717.52 555.88 1.291 0.244281
## Week_4 -340.72 470.90 -0.724 0.496568
## Week_5 217.01 438.65 0.495 0.638393
## Week_6 -365.02 300.14 -1.216 0.269581
## Week_7 165.25 393.69 0.420 0.689288
## Week_8 29.36 404.02 0.073 0.944433
## Week_9 -166.57 638.68 -0.261 0.802968
## Week_10 -234.08 519.83 -0.450 0.668306
## Week_11 169.53 433.90 0.391 0.709506
## Week_12 262.84 509.01 0.516 0.624073
## Week_13 -1076.35 788.16 -1.366 0.221027
## Week_14 1078.02 681.16 1.583 0.164596
## Week_15 -1559.96 630.00 -2.476 0.048056 *
## Week_16 1827.43 558.70 3.271 0.017016 *
## Week_17 386.71 612.74 0.631 0.551235
## Week_18 -492.61 438.16 -1.124 0.303853
## Week_19 11.51 417.75 0.028 0.978914
## Week_20 989.29 386.49 2.560 0.042925 *
## Week_21 -57.21 450.56 -0.127 0.903112
## Week_22 436.35 515.92 0.846 0.430113
## Week_23 317.56 431.15 0.737 0.489182
## Week_24 -733.99 504.67 -1.454 0.196068
## Week_25 -240.76 448.57 -0.537 0.610760
## Week_26 209.51 159.87 1.311 0.237947
## Week_27 -14.21 757.91 -0.019 0.985648
## Week_28 -131.89 879.91 -0.150 0.885762
## Week_29 206.71 1097.98 0.188 0.856876
## Week_30 -974.75 861.81 -1.131 0.301207
## Week_31 1077.29 743.80 1.448 0.197681
## Week_32 947.29 1279.58 0.740 0.487056
## Week_33 -1773.74 952.46 -1.862 0.111871
## Week_34 3870.94 1476.55 2.622 0.039501 *
## Week_35 675.84 911.21 0.742 0.486281
## Week_36 -1057.40 807.72 -1.309 0.238394
## Week_37 317.53 712.30 0.446 0.671388
## Week_38 841.74 721.83 1.166 0.287815
## Week_39 -1685.51 744.97 -2.263 0.064326 .
## Week_40 103.02 851.37 0.121 0.907638
## Week_41 1151.08 840.81 1.369 0.220034
## Week_42 1809.87 1039.84 1.741 0.132413
## Week_43 -637.56 1133.74 -0.562 0.594247
## Week_44 724.07 490.91 1.475 0.190668
## Week_45 -1348.15 793.50 -1.699 0.140237
## Week_46 794.57 609.27 1.304 0.239978
## Week_47 -391.25 555.50 -0.704 0.507634
## Week_48 -284.07 453.62 -0.626 0.554229
## Week_49 380.32 425.45 0.894 0.405789
## Week_50 385.14 741.11 0.520 0.621892
## Week_51 -95.59 503.39 -0.190 0.855654
## Week_52 44.52 419.39 0.106 0.918929
## Week_53 -356.12 338.17 -1.053 0.332864
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4681 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9412, Adjusted R-squared: 0.4215
## F-statistic: 1.811 on 53 and 6 DF, p-value: 0.2339
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9439.1 -2055.9 -257.6 2199.7 7010.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 68156.459 21733.187 3.136 0.02017 *
## Week_1 2188.683 1224.726 1.787 0.12415
## Week_2 -1597.258 782.284 -2.042 0.08723 .
## Week_3 -942.923 1294.437 -0.728 0.49378
## Week_4 1141.234 1096.544 1.041 0.33810
## Week_5 -377.968 1021.447 -0.370 0.72407
## Week_6 848.260 698.902 1.214 0.27046
## Week_7 -2028.193 916.763 -2.212 0.06892 .
## Week_8 2191.678 940.812 2.330 0.05868 .
## Week_9 -1646.316 1487.251 -1.107 0.31071
## Week_10 -883.528 1210.498 -0.730 0.49296
## Week_11 227.101 1010.390 0.225 0.82962
## Week_12 1723.757 1185.298 1.454 0.19610
## Week_13 -2866.898 1835.322 -1.562 0.16930
## Week_14 2192.277 1586.166 1.382 0.21619
## Week_15 2605.230 1467.021 1.776 0.12610
## Week_16 236.891 1301.004 0.182 0.86151
## Week_17 -5458.131 1426.834 -3.825 0.00871 **
## Week_18 2930.105 1020.306 2.872 0.02836 *
## Week_19 379.006 972.781 0.390 0.71028
## Week_20 667.900 899.978 0.742 0.48603
## Week_21 319.439 1049.189 0.304 0.77106
## Week_22 -706.750 1201.390 -0.588 0.57780
## Week_23 576.682 1003.979 0.574 0.58657
## Week_24 -234.974 1175.183 -0.200 0.84813
## Week_25 -1749.385 1044.545 -1.675 0.14500
## Week_26 691.304 372.267 1.857 0.11269
## Week_27 -572.160 1764.893 -0.324 0.75680
## Week_28 -84.217 2048.967 -0.041 0.96855
## Week_29 1838.951 2556.769 0.719 0.49903
## Week_30 -1449.662 2006.826 -0.722 0.49725
## Week_31 -1477.208 1732.026 -0.853 0.42646
## Week_32 -1827.702 2979.662 -0.613 0.56213
## Week_33 3005.513 2217.924 1.355 0.22418
## Week_34 5139.220 3438.326 1.495 0.18562
## Week_35 1735.325 2121.874 0.818 0.44471
## Week_36 -4388.823 1880.883 -2.333 0.05837 .
## Week_37 2658.598 1658.667 1.603 0.16009
## Week_38 311.665 1680.862 0.185 0.85901
## Week_39 2190.043 1734.756 1.262 0.25363
## Week_40 -1424.282 1982.521 -0.718 0.49951
## Week_41 -3150.295 1957.938 -1.609 0.15874
## Week_42 -997.026 2421.387 -0.412 0.69482
## Week_43 -503.172 2640.060 -0.191 0.85513
## Week_44 810.417 1143.133 0.709 0.50496
## Week_45 -539.623 1847.769 -0.292 0.78009
## Week_46 -1509.091 1418.752 -1.064 0.32840
## Week_47 -667.043 1293.557 -0.516 0.62453
## Week_48 913.235 1056.311 0.865 0.42050
## Week_49 7.926 990.713 0.008 0.99388
## Week_50 979.602 1725.762 0.568 0.59087
## Week_51 -57.064 1172.212 -0.049 0.96275
## Week_52 2582.939 976.605 2.645 0.03829 *
## Week_53 -2250.581 787.479 -2.858 0.02888 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10900 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9517, Adjusted R-squared: 0.5249
## F-statistic: 2.23 on 53 and 6 DF, p-value: 0.1572
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5109.1 -1735.2 102.4 1843.0 6184.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 46765.75 15381.26 3.040 0.02279 *
## Week_1 934.18 866.78 1.078 0.32255
## Week_2 -124.30 553.65 -0.225 0.82981
## Week_3 -828.83 916.11 -0.905 0.40048
## Week_4 542.37 776.06 0.699 0.51079
## Week_5 -959.23 722.91 -1.327 0.23280
## Week_6 1208.17 494.63 2.443 0.05030 .
## Week_7 -566.20 648.82 -0.873 0.41640
## Week_8 -356.02 665.84 -0.535 0.61208
## Week_9 746.36 1052.57 0.709 0.50488
## Week_10 -184.80 856.71 -0.216 0.83636
## Week_11 -186.98 715.08 -0.261 0.80247
## Week_12 304.49 838.87 0.363 0.72907
## Week_13 -1704.26 1298.91 -1.312 0.23746
## Week_14 615.22 1122.58 0.548 0.60344
## Week_15 3881.69 1038.26 3.739 0.00964 **
## Week_16 -2124.09 920.76 -2.307 0.06053 .
## Week_17 -2163.89 1009.82 -2.143 0.07585 .
## Week_18 644.20 722.10 0.892 0.40668
## Week_19 572.37 688.47 0.831 0.43759
## Week_20 -1126.34 636.94 -1.768 0.12741
## Week_21 184.23 742.54 0.248 0.81233
## Week_22 -301.90 850.26 -0.355 0.73469
## Week_23 2346.29 710.55 3.302 0.01637 *
## Week_24 296.40 831.71 0.356 0.73376
## Week_25 -1459.61 739.26 -1.974 0.09576 .
## Week_26 130.54 263.46 0.495 0.63790
## Week_27 178.04 1249.07 0.143 0.89132
## Week_28 1385.44 1450.12 0.955 0.37627
## Week_29 -1226.06 1809.51 -0.678 0.52330
## Week_30 1847.09 1420.29 1.301 0.24114
## Week_31 -855.39 1225.81 -0.698 0.51141
## Week_32 -4285.81 2108.80 -2.032 0.08838 .
## Week_33 3378.40 1569.69 2.152 0.07487 .
## Week_34 1709.14 2433.41 0.702 0.50877
## Week_35 -2221.66 1501.72 -1.479 0.18952
## Week_36 -1743.00 1331.16 -1.309 0.23831
## Week_37 934.09 1173.89 0.796 0.45651
## Week_38 1060.48 1189.60 0.891 0.40701
## Week_39 1056.07 1227.74 0.860 0.42273
## Week_40 -238.15 1403.09 -0.170 0.87080
## Week_41 198.43 1385.69 0.143 0.89082
## Week_42 -2870.61 1713.69 -1.675 0.14493
## Week_43 4173.14 1868.45 2.233 0.06695 .
## Week_44 -820.15 809.03 -1.014 0.34983
## Week_45 -446.36 1307.72 -0.341 0.74449
## Week_46 -848.81 1004.10 -0.845 0.43033
## Week_47 1047.42 915.49 1.144 0.29616
## Week_48 -243.87 747.58 -0.326 0.75534
## Week_49 69.04 701.16 0.098 0.92477
## Week_50 -1356.34 1221.38 -1.111 0.30929
## Week_51 449.93 829.61 0.542 0.60712
## Week_52 1045.16 691.17 1.512 0.18125
## Week_53 -1220.27 557.32 -2.190 0.07112 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7715 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9336, Adjusted R-squared: 0.3473
## F-statistic: 1.592 on 53 and 6 DF, p-value: 0.2929
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10104.8 -2583.3 -389.8 3367.5 7371.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 96670.63 25554.74 3.783 0.00915 **
## Week_1 3451.33 1440.08 2.397 0.05354 .
## Week_2 -1520.17 919.84 -1.653 0.14949
## Week_3 -1670.56 1522.05 -1.098 0.31447
## Week_4 2831.99 1289.36 2.196 0.07045 .
## Week_5 -2441.82 1201.06 -2.033 0.08829 .
## Week_6 70.14 821.80 0.085 0.93476
## Week_7 -398.52 1077.97 -0.370 0.72430
## Week_8 1010.82 1106.24 0.914 0.39609
## Week_9 -764.43 1748.77 -0.437 0.67731
## Week_10 -188.55 1423.35 -0.132 0.89894
## Week_11 -1134.97 1188.06 -0.955 0.37631
## Week_12 1074.31 1393.72 0.771 0.47007
## Week_13 -1405.91 2158.04 -0.651 0.53888
## Week_14 2414.63 1865.08 1.295 0.24303
## Week_15 3325.83 1724.98 1.928 0.10212
## Week_16 1678.40 1529.77 1.097 0.31464
## Week_17 -7583.73 1677.73 -4.520 0.00402 **
## Week_18 1082.16 1199.72 0.902 0.40181
## Week_19 1245.47 1143.83 1.089 0.31801
## Week_20 1453.33 1058.23 1.373 0.21875
## Week_21 753.84 1233.68 0.611 0.56358
## Week_22 -2476.33 1412.64 -1.753 0.13015
## Week_23 189.76 1180.52 0.161 0.87757
## Week_24 1236.00 1381.83 0.894 0.40552
## Week_25 -2461.33 1228.22 -2.004 0.09192 .
## Week_26 919.70 437.73 2.101 0.08036 .
## Week_27 1493.06 2075.23 0.719 0.49890
## Week_28 533.91 2409.26 0.222 0.83197
## Week_29 2307.32 3006.35 0.767 0.47191
## Week_30 -2755.85 2359.70 -1.168 0.28716
## Week_31 149.63 2036.58 0.073 0.94382
## Week_32 439.09 3503.60 0.125 0.90436
## Week_33 3293.80 2607.92 1.263 0.25345
## Week_34 4976.79 4042.92 1.231 0.26439
## Week_35 4389.25 2494.98 1.759 0.12903
## Week_36 -10722.99 2211.62 -4.848 0.00286 **
## Week_37 3373.03 1950.33 1.729 0.13445
## Week_38 1223.21 1976.42 0.619 0.55873
## Week_39 1973.64 2039.79 0.968 0.37063
## Week_40 -761.51 2331.13 -0.327 0.75501
## Week_41 -2030.78 2302.22 -0.882 0.41167
## Week_42 -1113.27 2847.16 -0.391 0.70930
## Week_43 1810.92 3104.29 0.583 0.58090
## Week_44 1513.11 1344.14 1.126 0.30329
## Week_45 -3075.01 2172.68 -1.415 0.20673
## Week_46 -537.24 1668.22 -0.322 0.75835
## Week_47 1197.76 1521.02 0.787 0.46097
## Week_48 320.67 1242.05 0.258 0.80490
## Week_49 -1484.16 1164.92 -1.274 0.24977
## Week_50 2038.08 2029.22 1.004 0.35397
## Week_51 951.15 1378.33 0.690 0.51594
## Week_52 1096.07 1148.33 0.954 0.37669
## Week_53 -1152.40 925.95 -1.245 0.25970
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12820 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.953, Adjusted R-squared: 0.5378
## F-statistic: 2.295 on 53 and 6 DF, p-value: 0.1483
Abbotsford monthly
## [1] "There are 6 NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -83128 -40055 -1379 28889 110283
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 139811.0 7999.8 17.477 <2e-16 ***
## Month_1 521.0 884.1 0.589 0.5583
## Month_2 -913.1 1016.1 -0.899 0.3732
## Month_3 997.3 785.2 1.270 0.2101
## Month_4 1051.4 607.8 1.730 0.0900 .
## Month_5 936.8 511.1 1.833 0.0729 .
## Month_6 621.2 320.9 1.936 0.0587 .
## Month_7 1063.9 478.5 2.223 0.0308 *
## Month_8 1917.5 1178.1 1.628 0.1100
## Month_9 4248.3 1656.4 2.565 0.0134 *
## Month_10 -2634.4 2914.7 -0.904 0.3705
## Month_11 -1132.8 2020.3 -0.561 0.5776
## Month_12 415.0 1048.2 0.396 0.6939
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 47600 on 49 degrees of freedom
## Multiple R-squared: 0.4567, Adjusted R-squared: 0.3237
## F-statistic: 3.433 on 12 and 49 DF, p-value: 0.001068
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10085.2 -3371.7 504.3 3570.7 11400.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24425.49 919.85 26.554 <2e-16 ***
## Month_1 -49.89 101.66 -0.491 0.6258
## Month_2 -29.44 116.83 -0.252 0.8021
## Month_3 199.03 90.29 2.204 0.0322 *
## Month_4 120.83 69.89 1.729 0.0901 .
## Month_5 97.11 58.77 1.652 0.1048
## Month_6 18.59 36.90 0.504 0.6167
## Month_7 63.99 55.02 1.163 0.2505
## Month_8 311.02 135.46 2.296 0.0260 *
## Month_9 339.10 190.46 1.780 0.0812 .
## Month_10 -445.52 335.15 -1.329 0.1899
## Month_11 -236.64 232.31 -1.019 0.3134
## Month_12 54.12 120.53 0.449 0.6554
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5474 on 49 degrees of freedom
## Multiple R-squared: 0.3811, Adjusted R-squared: 0.2296
## F-statistic: 2.515 on 12 and 49 DF, p-value: 0.01158
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31122 -8239 -518 7236 32357
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60095.97 2409.55 24.941 <2e-16 ***
## Month_1 191.94 266.29 0.721 0.4745
## Month_2 -270.34 306.04 -0.883 0.3814
## Month_3 383.27 236.50 1.621 0.1115
## Month_4 244.95 183.08 1.338 0.1871
## Month_5 179.89 153.95 1.169 0.2483
## Month_6 242.49 96.66 2.509 0.0155 *
## Month_7 369.64 144.12 2.565 0.0134 *
## Month_8 912.49 354.85 2.572 0.0132 *
## Month_9 934.74 498.91 1.874 0.0670 .
## Month_10 -1069.26 877.91 -1.218 0.2291
## Month_11 -405.27 608.52 -0.666 0.5085
## Month_12 359.04 315.73 1.137 0.2610
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14340 on 49 degrees of freedom
## Multiple R-squared: 0.493, Adjusted R-squared: 0.3689
## F-statistic: 3.971 on 12 and 49 DF, p-value: 0.0002775
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -16719.9 -4951.4 841.6 4278.2 14175.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 92702.49 1276.14 72.643 < 2e-16 ***
## Month_1 125.12 141.03 0.887 0.379328
## Month_2 -19.87 162.09 -0.123 0.902953
## Month_3 330.37 125.26 2.638 0.011158 *
## Month_4 115.13 96.96 1.187 0.240819
## Month_5 -77.89 81.53 -0.955 0.344081
## Month_6 14.04 51.19 0.274 0.785021
## Month_7 301.68 76.33 3.953 0.000248 ***
## Month_8 -233.37 187.93 -1.242 0.220240
## Month_9 329.03 264.23 1.245 0.218975
## Month_10 -398.92 464.96 -0.858 0.395088
## Month_11 745.00 322.28 2.312 0.025044 *
## Month_12 -89.07 167.22 -0.533 0.596675
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7594 on 49 degrees of freedom
## Multiple R-squared: 0.4863, Adjusted R-squared: 0.3605
## F-statistic: 3.865 on 12 and 49 DF, p-value: 0.0003605
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12660.6 -3094.1 227.8 2645.3 12989.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 19311.52 958.64 20.145 <2e-16 ***
## Month_1 -32.93 105.94 -0.311 0.7572
## Month_2 -66.48 121.76 -0.546 0.5876
## Month_3 142.65 94.09 1.516 0.1359
## Month_4 93.74 72.84 1.287 0.2042
## Month_5 110.53 61.25 1.805 0.0773 .
## Month_6 49.61 38.45 1.290 0.2030
## Month_7 68.37 57.34 1.192 0.2388
## Month_8 370.36 141.18 2.623 0.0116 *
## Month_9 246.75 198.49 1.243 0.2197
## Month_10 -445.42 349.28 -1.275 0.2082
## Month_11 -217.27 242.10 -0.897 0.3739
## Month_12 102.03 125.61 0.812 0.4206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5705 on 49 degrees of freedom
## Multiple R-squared: 0.3678, Adjusted R-squared: 0.213
## F-statistic: 2.376 on 12 and 49 DF, p-value: 0.01669
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11931.2 -3416.9 40.2 2467.4 17139.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 27981.612 1068.006 26.200 <2e-16 ***
## Month_1 -134.482 118.031 -1.139 0.2601
## Month_2 -140.207 135.650 -1.034 0.3064
## Month_3 128.518 104.827 1.226 0.2261
## Month_4 -4.936 81.148 -0.061 0.9517
## Month_5 63.461 68.235 0.930 0.3569
## Month_6 24.973 42.841 0.583 0.5626
## Month_7 -11.757 63.879 -0.184 0.8547
## Month_8 274.108 157.282 1.743 0.0876 .
## Month_9 95.019 221.137 0.430 0.6693
## Month_10 177.198 389.125 0.455 0.6509
## Month_11 114.656 269.721 0.425 0.6726
## Month_12 84.667 139.945 0.605 0.5480
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6355 on 49 degrees of freedom
## Multiple R-squared: 0.1769, Adjusted R-squared: -0.02462
## F-statistic: 0.8778 on 12 and 49 DF, p-value: 0.5741
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31537 -7471 2092 9153 29061
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 67700.54 2429.09 27.871 < 2e-16 ***
## Month_1 -125.34 268.45 -0.467 0.64264
## Month_2 -66.19 308.52 -0.215 0.83103
## Month_3 302.17 238.42 1.267 0.21101
## Month_4 286.12 184.56 1.550 0.12752
## Month_5 52.63 155.20 0.339 0.73598
## Month_6 4.35 97.44 0.045 0.96458
## Month_7 -46.82 145.29 -0.322 0.74861
## Month_8 594.42 357.73 1.662 0.10296
## Month_9 1551.98 502.96 3.086 0.00334 **
## Month_10 -1242.53 885.03 -1.404 0.16664
## Month_11 264.68 613.46 0.431 0.66803
## Month_12 -208.75 318.29 -0.656 0.51499
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14450 on 49 degrees of freedom
## Multiple R-squared: 0.3792, Adjusted R-squared: 0.2272
## F-statistic: 2.495 on 12 and 49 DF, p-value: 0.01222
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17820.0 -6968.2 -405.4 5302.3 20617.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 43135.53 1619.08 26.642 <2e-16 ***
## Month_1 -44.55 178.93 -0.249 0.8044
## Month_2 47.11 205.64 0.229 0.8198
## Month_3 207.05 158.92 1.303 0.1987
## Month_4 98.80 123.02 0.803 0.4258
## Month_5 130.06 103.44 1.257 0.2146
## Month_6 10.29 64.95 0.159 0.8747
## Month_7 11.01 96.84 0.114 0.9099
## Month_8 263.14 238.44 1.104 0.2752
## Month_9 599.14 335.24 1.787 0.0801 .
## Month_10 -107.63 589.91 -0.182 0.8560
## Month_11 -349.29 408.89 -0.854 0.3971
## Month_12 15.50 212.15 0.073 0.9421
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9635 on 49 degrees of freedom
## Multiple R-squared: 0.1837, Adjusted R-squared: -0.01622
## F-statistic: 0.9188 on 12 and 49 DF, p-value: 0.5357
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27165 -9654 295 7836 37911
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 42305.30 2599.62 16.274 < 2e-16 ***
## Month_1 92.96 287.30 0.324 0.74764
## Month_2 -190.45 330.18 -0.577 0.56672
## Month_3 570.16 255.16 2.235 0.03004 *
## Month_4 244.04 197.52 1.236 0.22253
## Month_5 198.78 166.09 1.197 0.23713
## Month_6 202.15 104.28 1.939 0.05833 .
## Month_7 239.27 155.49 1.539 0.13027
## Month_8 803.04 382.84 2.098 0.04112 *
## Month_9 1796.15 538.27 3.337 0.00162 **
## Month_10 -1200.40 947.16 -1.267 0.21102
## Month_11 74.77 656.52 0.114 0.90979
## Month_12 263.92 340.64 0.775 0.44219
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15470 on 49 degrees of freedom
## Multiple R-squared: 0.5022, Adjusted R-squared: 0.3803
## F-statistic: 4.12 on 12 and 49 DF, p-value: 0.0001929
Abbotsford monthly
## [1] "There are 7 NA in the matrix X in Kelowna station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -97125 -39427 -8252 36192 95814
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 166461.3 9204.8 18.084 <2e-16 ***
## Month_1 -584.5 1010.2 -0.579 0.566
## Month_2 -1794.7 1137.4 -1.578 0.121
## Month_3 1236.4 917.6 1.347 0.184
## Month_4 -183.6 1047.9 -0.175 0.862
## Month_5 654.3 617.5 1.060 0.295
## Month_6 441.2 569.6 0.775 0.442
## Month_7 235.5 1024.4 0.230 0.819
## Month_8 5077.8 3179.3 1.597 0.117
## Month_9 6652.6 3152.1 2.111 0.040 *
## Month_10 -3069.9 3334.4 -0.921 0.362
## Month_11 418.4 1427.3 0.293 0.771
## Month_12 -453.8 994.0 -0.457 0.650
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 53640 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3101, Adjusted R-squared: 0.1377
## F-statistic: 1.798 on 12 and 48 DF, p-value: 0.0755
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11224.6 -3693.7 300.7 3662.8 11372.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 26403.302 948.583 27.834 <2e-16 ***
## Month_1 -200.357 104.108 -1.925 0.0602 .
## Month_2 -223.187 117.207 -1.904 0.0629 .
## Month_3 174.251 94.562 1.843 0.0716 .
## Month_4 -38.479 107.990 -0.356 0.7232
## Month_5 112.974 63.637 1.775 0.0822 .
## Month_6 1.435 58.699 0.024 0.9806
## Month_7 -28.891 105.571 -0.274 0.7855
## Month_8 669.822 327.639 2.044 0.0464 *
## Month_9 433.011 324.832 1.333 0.1888
## Month_10 -215.774 343.622 -0.628 0.5330
## Month_11 -84.118 147.083 -0.572 0.5701
## Month_12 -12.822 102.433 -0.125 0.9009
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5528 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3804, Adjusted R-squared: 0.2255
## F-statistic: 2.455 on 12 and 48 DF, p-value: 0.01382
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31413 -12170 -2894 9570 31001
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 68017.23 2788.52 24.392 <2e-16 ***
## Month_1 -367.68 306.04 -1.201 0.2355
## Month_2 -626.16 344.55 -1.817 0.0754 .
## Month_3 559.18 277.98 2.012 0.0499 *
## Month_4 -273.11 317.45 -0.860 0.3939
## Month_5 144.34 187.07 0.772 0.4442
## Month_6 168.89 172.56 0.979 0.3326
## Month_7 350.62 310.34 1.130 0.2642
## Month_8 1469.29 963.15 1.526 0.1337
## Month_9 1916.71 954.90 2.007 0.0504 .
## Month_10 -343.77 1010.13 -0.340 0.7351
## Month_11 73.32 432.38 0.170 0.8661
## Month_12 78.94 301.12 0.262 0.7943
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 16250 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3577, Adjusted R-squared: 0.1971
## F-statistic: 2.227 on 12 and 48 DF, p-value: 0.02505
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14153 -5490 -1262 5376 22646
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 94200.881 1622.263 58.068 <2e-16 ***
## Month_1 54.751 178.045 0.308 0.760
## Month_2 -165.778 200.447 -0.827 0.412
## Month_3 157.115 161.720 0.972 0.336
## Month_4 78.341 184.683 0.424 0.673
## Month_5 4.315 108.833 0.040 0.969
## Month_6 -113.398 100.387 -1.130 0.264
## Month_7 208.230 180.547 1.153 0.254
## Month_8 574.145 560.326 1.025 0.311
## Month_9 182.230 555.527 0.328 0.744
## Month_10 -940.413 587.661 -1.600 0.116
## Month_11 347.187 251.542 1.380 0.174
## Month_12 -104.652 175.180 -0.597 0.553
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9453 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.2174, Adjusted R-squared: 0.02179
## F-statistic: 1.111 on 12 and 48 DF, p-value: 0.3733
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11209.8 -3796.6 -377.4 3152.6 15151.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 21464.44 1038.86 20.662 <2e-16 ***
## Month_1 -140.29 114.02 -1.230 0.2245
## Month_2 -213.08 128.36 -1.660 0.1034
## Month_3 180.26 103.56 1.741 0.0882 .
## Month_4 -174.68 118.27 -1.477 0.1462
## Month_5 54.74 69.69 0.785 0.4361
## Month_6 54.42 64.29 0.847 0.4015
## Month_7 -18.26 115.62 -0.158 0.8752
## Month_8 512.06 358.82 1.427 0.1600
## Month_9 610.33 355.75 1.716 0.0927 .
## Month_10 -258.02 376.32 -0.686 0.4962
## Month_11 -74.84 161.08 -0.465 0.6443
## Month_12 -17.72 112.18 -0.158 0.8751
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6054 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3007, Adjusted R-squared: 0.1259
## F-statistic: 1.72 on 12 and 48 DF, p-value: 0.09187
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13918.5 -3792.6 -126.6 1995.7 16782.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 29365.79 1131.82 25.946 <2e-16 ***
## Month_1 -107.59 124.22 -0.866 0.391
## Month_2 -88.39 139.85 -0.632 0.530
## Month_3 83.94 112.83 0.744 0.461
## Month_4 48.09 128.85 0.373 0.711
## Month_5 -77.52 75.93 -1.021 0.312
## Month_6 112.42 70.04 1.605 0.115
## Month_7 -23.60 125.96 -0.187 0.852
## Month_8 236.91 390.93 0.606 0.547
## Month_9 166.80 387.58 0.430 0.669
## Month_10 172.64 410.00 0.421 0.676
## Month_11 -107.09 175.50 -0.610 0.545
## Month_12 28.53 122.22 0.233 0.816
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6595 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.1298, Adjusted R-squared: -0.08779
## F-statistic: 0.5965 on 12 and 48 DF, p-value: 0.8341
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -37202 -7839 1099 8652 23218
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 71851.85 2561.83 28.047 <2e-16 ***
## Month_1 -405.20 281.16 -1.441 0.1560
## Month_2 -577.77 316.54 -1.825 0.0742 .
## Month_3 14.96 255.38 0.059 0.9535
## Month_4 344.61 291.65 1.182 0.2432
## Month_5 341.17 171.87 1.985 0.0529 .
## Month_6 25.43 158.53 0.160 0.8732
## Month_7 -184.93 285.11 -0.649 0.5197
## Month_8 2262.38 884.85 2.557 0.0138 *
## Month_9 899.62 877.27 1.025 0.3103
## Month_10 -255.89 928.02 -0.276 0.7839
## Month_11 410.47 397.23 1.033 0.3066
## Month_12 42.58 276.64 0.154 0.8783
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14930 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3514, Adjusted R-squared: 0.1892
## F-statistic: 2.167 on 12 and 48 DF, p-value: 0.02931
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14682.6 -7423.7 -193.1 6081.1 18921.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 45912.01 1489.48 30.824 < 2e-16 ***
## Month_1 -162.22 163.47 -0.992 0.32600
## Month_2 -150.52 184.04 -0.818 0.41748
## Month_3 162.41 148.48 1.094 0.27950
## Month_4 350.11 169.57 2.065 0.04437 *
## Month_5 269.45 99.92 2.697 0.00963 **
## Month_6 -36.11 92.17 -0.392 0.69699
## Month_7 -17.82 165.77 -0.107 0.91485
## Month_8 224.31 514.46 0.436 0.66479
## Month_9 463.59 510.06 0.909 0.36794
## Month_10 546.11 539.56 1.012 0.31655
## Month_11 42.36 230.95 0.183 0.85524
## Month_12 -178.26 160.84 -1.108 0.27326
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8679 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.335, Adjusted R-squared: 0.1687
## F-statistic: 2.015 on 12 and 48 DF, p-value: 0.04345
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -36558 -7983 -761 7877 32691
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 50249.40 2897.35 17.343 <2e-16 ***
## Month_1 -353.10 317.99 -1.110 0.2723
## Month_2 -753.93 358.00 -2.106 0.0405 *
## Month_3 344.17 288.83 1.192 0.2393
## Month_4 -26.56 329.84 -0.081 0.9362
## Month_5 393.99 194.37 2.027 0.0482 *
## Month_6 137.54 179.29 0.767 0.4468
## Month_7 183.98 322.45 0.571 0.5710
## Month_8 2159.48 1000.74 2.158 0.0360 *
## Month_9 2334.12 992.17 2.353 0.0228 *
## Month_10 -803.95 1049.56 -0.766 0.4474
## Month_11 321.73 449.25 0.716 0.4774
## Month_12 190.80 312.87 0.610 0.5448
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 16880 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.4155, Adjusted R-squared: 0.2694
## F-statistic: 2.844 on 12 and 48 DF, p-value: 0.005024
linear reg for yield VS daily Max Temp
Abbotsford
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27887.8 -8791.8 -970.2 9462.8 30817.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -379410.47 216422.90 -1.753 0.1177
## Week_1 5569.15 3867.69 1.440 0.1879
## Week_2 4633.31 4580.18 1.012 0.3413
## Week_3 -3710.64 4951.29 -0.749 0.4751
## Week_4 27.95 4122.76 0.007 0.9948
## Week_5 487.06 4704.67 0.104 0.9201
## Week_6 -1109.62 6349.16 -0.175 0.8656
## Week_7 2491.88 5178.18 0.481 0.6432
## Week_8 1956.54 8225.02 0.238 0.8180
## Week_9 -2324.53 4514.65 -0.515 0.6206
## Week_10 -3040.07 7166.04 -0.424 0.6826
## Week_11 -15492.00 11097.32 -1.396 0.2002
## Week_12 6499.98 7199.61 0.903 0.3930
## Week_13 8247.42 11298.69 0.730 0.4862
## Week_14 -9458.74 16998.02 -0.556 0.5931
## Week_15 8600.07 10328.70 0.833 0.4292
## Week_16 -1342.51 6477.99 -0.207 0.8410
## Week_17 11582.98 7095.79 1.632 0.1412
## Week_18 6484.74 7605.25 0.853 0.4186
## Week_19 1256.56 6470.79 0.194 0.8509
## Week_20 7659.30 7092.90 1.080 0.3117
## Week_21 2722.31 7773.04 0.350 0.7352
## Week_22 -4391.71 7022.84 -0.625 0.5492
## Week_23 181.00 6893.98 0.026 0.9797
## Week_24 -7746.16 6029.18 -1.285 0.2348
## Week_25 2684.34 7933.91 0.338 0.7438
## Week_26 1207.84 7960.36 0.152 0.8832
## Week_27 10662.66 11377.60 0.937 0.3761
## Week_28 3922.51 9126.18 0.430 0.6787
## Week_29 -12120.23 9269.33 -1.308 0.2273
## Week_30 8497.35 8158.22 1.042 0.3281
## Week_31 10183.10 7471.30 1.363 0.2100
## Week_32 -6251.69 4441.55 -1.408 0.1969
## Week_33 -12660.54 8296.48 -1.526 0.1655
## Week_34 24884.44 8528.16 2.918 0.0194 *
## Week_35 -4741.30 5859.62 -0.809 0.4418
## Week_36 3778.39 7869.29 0.480 0.6440
## Week_37 2959.59 9376.17 0.316 0.7603
## Week_38 477.54 8461.64 0.056 0.9564
## Week_39 -11950.24 8350.59 -1.431 0.1903
## Week_40 6703.27 7324.00 0.915 0.3868
## Week_41 -10685.91 8618.50 -1.240 0.2502
## Week_42 8432.17 8595.78 0.981 0.3553
## Week_43 1782.38 6710.56 0.266 0.7973
## Week_44 -4602.96 4994.26 -0.922 0.3837
## Week_45 -10205.91 7467.38 -1.367 0.2089
## Week_46 9118.57 6963.67 1.309 0.2267
## Week_47 -2333.68 4243.52 -0.550 0.5974
## Week_48 751.76 7298.11 0.103 0.9205
## Week_49 697.45 3835.69 0.182 0.8602
## Week_50 -2093.30 4034.65 -0.519 0.6179
## Week_51 -4463.51 4658.36 -0.958 0.3660
## Week_52 6020.65 6413.27 0.939 0.3753
## Week_53 -1509.30 3352.33 -0.450 0.6645
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 39000 on 8 degrees of freedom
## Multiple R-squared: 0.9405, Adjusted R-squared: 0.5459
## F-statistic: 2.384 on 53 and 8 DF, p-value: 0.09579
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4204.1 -1123.1 117.2 1306.2 3614.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -13226.592 28152.253 -0.470 0.6510
## Week_1 -206.202 503.109 -0.410 0.6927
## Week_2 471.703 595.789 0.792 0.4514
## Week_3 -430.418 644.063 -0.668 0.5228
## Week_4 460.727 536.288 0.859 0.4153
## Week_5 -353.637 611.982 -0.578 0.5793
## Week_6 861.448 825.897 1.043 0.3274
## Week_7 267.191 673.576 0.397 0.7020
## Week_8 -383.405 1069.908 -0.358 0.7294
## Week_9 484.765 587.265 0.825 0.4330
## Week_10 -2000.691 932.157 -2.146 0.0641 .
## Week_11 -971.361 1443.538 -0.673 0.5200
## Week_12 1229.279 936.524 1.313 0.2257
## Week_13 -672.262 1469.731 -0.457 0.6595
## Week_14 -642.650 2211.100 -0.291 0.7787
## Week_15 2896.384 1343.555 2.156 0.0632 .
## Week_16 -314.541 842.656 -0.373 0.7186
## Week_17 1648.437 923.019 1.786 0.1119
## Week_18 755.261 989.290 0.763 0.4671
## Week_19 1460.848 841.719 1.736 0.1209
## Week_20 550.243 922.643 0.596 0.5674
## Week_21 -2.594 1011.116 -0.003 0.9980
## Week_22 959.620 913.529 1.050 0.3242
## Week_23 -113.083 896.768 -0.126 0.9028
## Week_24 -1104.231 784.275 -1.408 0.1968
## Week_25 -914.571 1032.042 -0.886 0.4014
## Week_26 772.857 1035.482 0.746 0.4768
## Week_27 1194.739 1479.997 0.807 0.4429
## Week_28 -243.264 1187.132 -0.205 0.8428
## Week_29 -2210.946 1205.753 -1.834 0.1041
## Week_30 265.191 1061.220 0.250 0.8090
## Week_31 226.036 971.866 0.233 0.8219
## Week_32 515.944 577.756 0.893 0.3979
## Week_33 -795.922 1079.205 -0.738 0.4819
## Week_34 3514.440 1109.341 3.168 0.0132 *
## Week_35 -396.296 762.219 -0.520 0.6172
## Week_36 -1025.491 1023.636 -1.002 0.3458
## Week_37 -345.374 1219.650 -0.283 0.7842
## Week_38 1584.012 1100.689 1.439 0.1881
## Week_39 -1461.904 1086.243 -1.346 0.2152
## Week_40 778.879 952.705 0.818 0.4373
## Week_41 -1850.641 1121.093 -1.651 0.1374
## Week_42 -3.340 1118.138 -0.003 0.9977
## Week_43 40.480 872.908 0.046 0.9641
## Week_44 -631.555 649.653 -0.972 0.3595
## Week_45 -2162.071 971.355 -2.226 0.0567 .
## Week_46 1061.800 905.833 1.172 0.2748
## Week_47 -344.553 551.996 -0.624 0.5499
## Week_48 -614.060 949.336 -0.647 0.5359
## Week_49 90.030 498.946 0.180 0.8613
## Week_50 125.258 524.826 0.239 0.8174
## Week_51 -41.222 605.959 -0.068 0.9474
## Week_52 634.156 834.237 0.760 0.4690
## Week_53 -183.356 436.071 -0.420 0.6852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5074 on 8 degrees of freedom
## Multiple R-squared: 0.9132, Adjusted R-squared: 0.3381
## F-statistic: 1.588 on 53 and 8 DF, p-value: 0.2509
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8212.3 -3126.3 -288.8 2799.6 7937.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -95390.10 59691.64 -1.598 0.1487
## Week_1 750.61 1066.75 0.704 0.5016
## Week_2 1107.53 1263.26 0.877 0.4062
## Week_3 -1040.10 1365.62 -0.762 0.4681
## Week_4 1237.90 1137.10 1.089 0.3080
## Week_5 -1064.53 1297.60 -0.820 0.4358
## Week_6 594.68 1751.16 0.340 0.7429
## Week_7 530.56 1428.19 0.371 0.7199
## Week_8 366.48 2268.54 0.162 0.8757
## Week_9 -624.03 1245.19 -0.501 0.6298
## Week_10 -2899.75 1976.47 -1.467 0.1805
## Week_11 -4937.88 3060.75 -1.613 0.1453
## Week_12 1578.46 1985.73 0.795 0.4496
## Week_13 2252.13 3116.29 0.723 0.4905
## Week_14 -2017.69 4688.23 -0.430 0.6783
## Week_15 2250.45 2848.76 0.790 0.4523
## Week_16 447.49 1786.70 0.250 0.8085
## Week_17 4306.02 1957.09 2.200 0.0590 .
## Week_18 1908.14 2097.61 0.910 0.3896
## Week_19 991.73 1784.71 0.556 0.5936
## Week_20 1918.57 1956.29 0.981 0.3555
## Week_21 -42.95 2143.88 -0.020 0.9845
## Week_22 168.93 1936.97 0.087 0.9326
## Week_23 -510.02 1901.43 -0.268 0.7953
## Week_24 -2308.19 1662.91 -1.388 0.2026
## Week_25 -978.05 2188.25 -0.447 0.6668
## Week_26 1289.66 2195.55 0.587 0.5731
## Week_27 4283.96 3138.06 1.365 0.2094
## Week_28 1816.04 2517.09 0.721 0.4912
## Week_29 -3301.41 2556.58 -1.291 0.2326
## Week_30 2132.15 2250.12 0.948 0.3711
## Week_31 1333.15 2060.66 0.647 0.5358
## Week_32 -970.70 1225.02 -0.792 0.4510
## Week_33 -2056.35 2288.25 -0.899 0.3951
## Week_34 7513.20 2352.15 3.194 0.0127 *
## Week_35 -2363.57 1616.14 -1.462 0.1818
## Week_36 1555.51 2170.43 0.717 0.4940
## Week_37 -1101.11 2586.04 -0.426 0.6815
## Week_38 1467.94 2333.81 0.629 0.5469
## Week_39 -4355.88 2303.18 -1.891 0.0952 .
## Week_40 1979.71 2020.03 0.980 0.3558
## Week_41 -2932.57 2377.07 -1.234 0.2523
## Week_42 2021.47 2370.80 0.853 0.4186
## Week_43 -137.38 1850.84 -0.074 0.9427
## Week_44 -533.27 1377.47 -0.387 0.7087
## Week_45 -4128.94 2059.58 -2.005 0.0799 .
## Week_46 3252.47 1920.65 1.693 0.1288
## Week_47 -977.19 1170.40 -0.835 0.4280
## Week_48 55.03 2012.89 0.027 0.9789
## Week_49 -99.20 1057.92 -0.094 0.9276
## Week_50 303.35 1112.80 0.273 0.7921
## Week_51 -1293.32 1284.82 -1.007 0.3436
## Week_52 2003.27 1768.85 1.133 0.2902
## Week_53 -1053.95 924.61 -1.140 0.2873
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10760 on 8 degrees of freedom
## Multiple R-squared: 0.9534, Adjusted R-squared: 0.6447
## F-statistic: 3.089 on 53 and 8 DF, p-value: 0.04663
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5074.5 -1479.5 83.5 1702.3 5149.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2186.260 31963.754 -0.068 0.9471
## Week_1 934.411 571.224 1.636 0.1405
## Week_2 -5.987 676.452 -0.009 0.9932
## Week_3 -303.844 731.262 -0.416 0.6887
## Week_4 -341.289 608.895 -0.561 0.5905
## Week_5 -19.539 694.838 -0.028 0.9783
## Week_6 -437.527 937.715 -0.467 0.6532
## Week_7 -468.809 764.771 -0.613 0.5569
## Week_8 -149.493 1214.762 -0.123 0.9051
## Week_9 -3.953 666.774 -0.006 0.9954
## Week_10 -192.018 1058.361 -0.181 0.8605
## Week_11 -120.229 1638.977 -0.073 0.9433
## Week_12 158.598 1063.319 0.149 0.8851
## Week_13 704.678 1668.717 0.422 0.6839
## Week_14 2715.992 2510.458 1.082 0.3108
## Week_15 -328.866 1525.457 -0.216 0.8347
## Week_16 119.674 956.743 0.125 0.9035
## Week_17 1498.923 1047.986 1.430 0.1905
## Week_18 -1482.445 1123.229 -1.320 0.2234
## Week_19 -465.128 955.679 -0.487 0.6395
## Week_20 943.113 1047.558 0.900 0.3943
## Week_21 -148.495 1148.010 -0.129 0.9003
## Week_22 -286.892 1037.211 -0.277 0.7891
## Week_23 638.609 1018.180 0.627 0.5480
## Week_24 -992.207 890.457 -1.114 0.2975
## Week_25 1731.828 1171.769 1.478 0.1777
## Week_26 -1720.659 1175.674 -1.464 0.1815
## Week_27 2407.086 1680.372 1.432 0.1899
## Week_28 1175.362 1347.856 0.872 0.4086
## Week_29 245.021 1368.999 0.179 0.8624
## Week_30 675.510 1204.897 0.561 0.5904
## Week_31 1373.139 1103.446 1.244 0.2486
## Week_32 -115.916 655.978 -0.177 0.8641
## Week_33 -2464.103 1225.317 -2.011 0.0792 .
## Week_34 910.440 1259.533 0.723 0.4904
## Week_35 -15.881 865.415 -0.018 0.9858
## Week_36 -1366.769 1162.225 -1.176 0.2734
## Week_37 -259.754 1384.777 -0.188 0.8559
## Week_38 293.554 1249.710 0.235 0.8202
## Week_39 -12.326 1233.308 -0.010 0.9923
## Week_40 1340.438 1081.690 1.239 0.2504
## Week_41 -266.946 1272.877 -0.210 0.8391
## Week_42 840.961 1269.521 0.662 0.5263
## Week_43 1257.420 991.090 1.269 0.2402
## Week_44 -1471.160 737.609 -1.994 0.0812 .
## Week_45 -1050.131 1102.866 -0.952 0.3689
## Week_46 2202.746 1028.472 2.142 0.0646 .
## Week_47 -198.656 626.730 -0.317 0.7594
## Week_48 1264.609 1077.866 1.173 0.2744
## Week_49 355.754 566.498 0.628 0.5475
## Week_50 334.252 595.882 0.561 0.5902
## Week_51 -546.703 687.999 -0.795 0.4498
## Week_52 109.568 947.184 0.116 0.9108
## Week_53 438.117 495.110 0.885 0.4020
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5761 on 8 degrees of freedom
## Multiple R-squared: 0.9517, Adjusted R-squared: 0.632
## F-statistic: 2.976 on 53 and 8 DF, p-value: 0.05191
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3638.5 -1138.7 -64.5 1057.1 3613.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -13620.06 26181.53 -0.520 0.6170
## Week_1 -170.93 467.89 -0.365 0.7243
## Week_2 387.58 554.08 0.699 0.5041
## Week_3 -766.01 598.98 -1.279 0.2368
## Week_4 566.51 498.75 1.136 0.2889
## Week_5 -374.77 569.14 -0.658 0.5287
## Week_6 494.10 768.08 0.643 0.5380
## Week_7 359.59 626.42 0.574 0.5817
## Week_8 -433.02 995.01 -0.435 0.6749
## Week_9 361.24 546.16 0.661 0.5269
## Week_10 -1921.02 866.90 -2.216 0.0575 .
## Week_11 -1680.93 1342.49 -1.252 0.2459
## Week_12 1524.00 870.97 1.750 0.1183
## Week_13 574.84 1366.85 0.421 0.6851
## Week_14 -2024.14 2056.32 -0.984 0.3538
## Week_15 2290.80 1249.50 1.833 0.1041
## Week_16 -644.50 783.67 -0.822 0.4347
## Week_17 1634.33 858.41 1.904 0.0934 .
## Week_18 1213.25 920.04 1.319 0.2238
## Week_19 868.42 782.80 1.109 0.2995
## Week_20 972.18 858.06 1.133 0.2900
## Week_21 -585.35 940.34 -0.622 0.5509
## Week_22 460.18 849.58 0.542 0.6028
## Week_23 68.34 833.99 0.082 0.9367
## Week_24 -1212.66 729.37 -1.663 0.1350
## Week_25 -953.90 959.80 -0.994 0.3494
## Week_26 929.03 963.00 0.965 0.3629
## Week_27 794.17 1376.39 0.577 0.5798
## Week_28 634.97 1104.03 0.575 0.5810
## Week_29 -2294.68 1121.35 -2.046 0.0749 .
## Week_30 403.28 986.93 0.409 0.6935
## Week_31 689.49 903.83 0.763 0.4674
## Week_32 241.33 537.31 0.449 0.6652
## Week_33 -738.99 1003.66 -0.736 0.4826
## Week_34 3245.97 1031.68 3.146 0.0137 *
## Week_35 -597.21 708.86 -0.842 0.4240
## Week_36 -692.89 951.98 -0.728 0.4875
## Week_37 -349.95 1134.27 -0.309 0.7656
## Week_38 1247.04 1023.64 1.218 0.2578
## Week_39 -1373.30 1010.20 -1.359 0.2111
## Week_40 106.14 886.01 0.120 0.9076
## Week_41 -1294.95 1042.61 -1.242 0.2494
## Week_42 530.63 1039.87 0.510 0.6236
## Week_43 222.70 811.80 0.274 0.7908
## Week_44 -66.02 604.18 -0.109 0.9157
## Week_45 -2097.31 903.36 -2.322 0.0488 *
## Week_46 1781.16 842.42 2.114 0.0674 .
## Week_47 -235.84 513.35 -0.459 0.6582
## Week_48 -616.75 882.88 -0.699 0.5046
## Week_49 -352.65 464.02 -0.760 0.4691
## Week_50 -146.35 488.09 -0.300 0.7719
## Week_51 150.73 563.54 0.267 0.7959
## Week_52 206.51 775.84 0.266 0.7968
## Week_53 -115.02 405.54 -0.284 0.7839
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4719 on 8 degrees of freedom
## Multiple R-squared: 0.9294, Adjusted R-squared: 0.4615
## F-statistic: 1.987 on 53 and 8 DF, p-value: 0.1517
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5846.3 -1290.8 -50.8 1531.9 4371.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2614.52 33260.31 0.079 0.9393
## Week_1 -677.65 594.40 -1.140 0.2872
## Week_2 -459.24 703.89 -0.652 0.5324
## Week_3 -386.17 760.92 -0.507 0.6255
## Week_4 1072.94 633.59 1.693 0.1288
## Week_5 -894.85 723.02 -1.238 0.2509
## Week_6 -484.15 975.75 -0.496 0.6331
## Week_7 745.73 795.79 0.937 0.3761
## Week_8 -1011.55 1264.04 -0.800 0.4467
## Week_9 -355.68 693.82 -0.513 0.6221
## Week_10 -830.61 1101.29 -0.754 0.4723
## Week_11 816.93 1705.46 0.479 0.6448
## Week_12 1693.65 1106.45 1.531 0.1644
## Week_13 -963.66 1736.41 -0.555 0.5941
## Week_14 2934.10 2612.29 1.123 0.2939
## Week_15 -766.97 1587.34 -0.483 0.6419
## Week_16 1045.38 995.55 1.050 0.3244
## Week_17 -227.59 1090.50 -0.209 0.8399
## Week_18 -2037.50 1168.79 -1.743 0.1195
## Week_19 358.32 994.44 0.360 0.7279
## Week_20 377.12 1090.05 0.346 0.7383
## Week_21 -1059.99 1194.58 -0.887 0.4008
## Week_22 -1251.47 1079.28 -1.160 0.2797
## Week_23 37.41 1059.48 0.035 0.9727
## Week_24 706.22 926.58 0.762 0.4678
## Week_25 801.80 1219.30 0.658 0.5293
## Week_26 511.63 1223.36 0.418 0.6868
## Week_27 -71.87 1748.53 -0.041 0.9682
## Week_28 1418.16 1402.53 1.011 0.3415
## Week_29 731.50 1424.53 0.514 0.6215
## Week_30 -1858.69 1253.77 -1.482 0.1765
## Week_31 -307.74 1148.21 -0.268 0.7955
## Week_32 74.90 682.59 0.110 0.9153
## Week_33 1348.41 1275.02 1.058 0.3211
## Week_34 390.25 1310.62 0.298 0.7735
## Week_35 -1038.43 900.52 -1.153 0.2821
## Week_36 -347.90 1209.37 -0.288 0.7809
## Week_37 -122.80 1440.95 -0.085 0.9342
## Week_38 251.42 1300.40 0.193 0.8515
## Week_39 -344.60 1283.34 -0.269 0.7951
## Week_40 -416.53 1125.57 -0.370 0.7209
## Week_41 476.62 1324.51 0.360 0.7283
## Week_42 1964.90 1321.02 1.487 0.1752
## Week_43 -1325.35 1031.29 -1.285 0.2347
## Week_44 1780.50 767.53 2.320 0.0489 *
## Week_45 -1894.00 1147.60 -1.650 0.1375
## Week_46 934.35 1070.19 0.873 0.4081
## Week_47 1417.49 652.15 2.174 0.0615 .
## Week_48 -107.34 1121.59 -0.096 0.9261
## Week_49 -844.77 589.48 -1.433 0.1897
## Week_50 -468.68 620.05 -0.756 0.4714
## Week_51 252.46 715.91 0.353 0.7335
## Week_52 -1091.62 985.60 -1.108 0.3002
## Week_53 177.79 515.19 0.345 0.7389
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5994 on 8 degrees of freedom
## Multiple R-squared: 0.8805, Adjusted R-squared: 0.08847
## F-statistic: 1.112 on 53 and 8 DF, p-value: 0.4763
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11813.4 -3030.8 397.2 3226.0 12447.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 93315.0390 74777.6071 1.248 0.2474
## Week_1 -419.4469 1336.3506 -0.314 0.7616
## Week_2 -1433.2573 1582.5262 -0.906 0.3916
## Week_3 2258.2339 1710.7507 1.320 0.2233
## Week_4 472.4900 1424.4800 0.332 0.7486
## Week_5 -1146.2948 1625.5386 -0.705 0.5007
## Week_6 353.8557 2193.7364 0.161 0.8759
## Week_7 16.4335 1789.1440 0.009 0.9929
## Week_8 -1803.9206 2841.8755 -0.635 0.5433
## Week_9 -480.1525 1559.8856 -0.308 0.7661
## Week_10 -3795.2263 2475.9821 -1.533 0.1639
## Week_11 -2046.9935 3834.3045 -0.534 0.6079
## Week_12 1572.8965 2487.5815 0.632 0.5448
## Week_13 -2297.9034 3903.8791 -0.589 0.5724
## Week_14 3461.4017 5873.0915 0.589 0.5719
## Week_15 6790.4379 3568.7313 1.903 0.0936 .
## Week_16 4154.3312 2238.2517 1.856 0.1005
## Week_17 3397.8516 2451.7104 1.386 0.2032
## Week_18 -1608.5163 2627.7381 -0.612 0.5574
## Week_19 943.7657 2235.7629 0.422 0.6841
## Week_20 1668.0157 2450.7102 0.681 0.5153
## Week_21 -945.4573 2685.7118 -0.352 0.7339
## Week_22 0.7152 2426.5036 0.000 0.9998
## Week_23 -1077.3680 2381.9820 -0.452 0.6631
## Week_24 -3291.8970 2083.1794 -1.580 0.1527
## Week_25 -3647.3402 2741.2940 -1.331 0.2200
## Week_26 4181.3355 2750.4315 1.520 0.1669
## Week_27 2963.2074 3931.1454 0.754 0.4726
## Week_28 1390.0122 3153.2425 0.441 0.6710
## Week_29 400.7122 3202.7046 0.125 0.9035
## Week_30 -1383.8310 2818.7972 -0.491 0.6367
## Week_31 -3047.3280 2581.4560 -1.180 0.2717
## Week_32 528.0668 1534.6270 0.344 0.7396
## Week_33 -808.6604 2866.5675 -0.282 0.7850
## Week_34 6494.5491 2946.6155 2.204 0.0586 .
## Week_35 1495.1868 2024.5950 0.739 0.4813
## Week_36 -128.2266 2718.9666 -0.047 0.9635
## Week_37 -5400.3101 3239.6164 -1.667 0.1341
## Week_38 4013.8240 2923.6343 1.373 0.2070
## Week_39 -6848.5002 2885.2634 -2.374 0.0450 *
## Week_40 350.0976 2530.5603 0.138 0.8934
## Week_41 -2519.6301 2977.8319 -0.846 0.4221
## Week_42 -677.9038 2969.9809 -0.228 0.8252
## Week_43 -5285.3740 2318.6053 -2.280 0.0521 .
## Week_44 -552.8590 1725.5989 -0.320 0.7569
## Week_45 -6062.1221 2580.1004 -2.350 0.0467 *
## Week_46 3191.7414 2406.0598 1.327 0.2213
## Week_47 -176.6592 1466.2031 -0.120 0.9071
## Week_48 1510.4028 2521.6136 0.599 0.5658
## Week_49 743.4374 1325.2938 0.561 0.5902
## Week_50 2045.2262 1394.0358 1.467 0.1805
## Week_51 -1932.5901 1609.5402 -1.201 0.2642
## Week_52 4028.7597 2215.8892 1.818 0.1066
## Week_53 -2245.1934 1158.2854 -1.938 0.0886 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13480 on 8 degrees of freedom
## Multiple R-squared: 0.9119, Adjusted R-squared: 0.3282
## F-statistic: 1.562 on 53 and 8 DF, p-value: 0.2595
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9762.3 -2100.8 230.9 2349.8 6195.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -61187.71 46168.70 -1.325 0.2217
## Week_1 1141.71 825.08 1.384 0.2038
## Week_2 2571.75 977.07 2.632 0.0301 *
## Week_3 -481.87 1056.24 -0.456 0.6604
## Week_4 -107.62 879.49 -0.122 0.9056
## Week_5 -212.14 1003.63 -0.211 0.8379
## Week_6 -450.96 1354.44 -0.333 0.7477
## Week_7 1304.39 1104.64 1.181 0.2716
## Week_8 1800.95 1754.61 1.026 0.3347
## Week_9 -1167.50 963.09 -1.212 0.2600
## Week_10 1605.93 1528.70 1.051 0.3242
## Week_11 -2342.20 2367.35 -0.989 0.3515
## Week_12 -2007.14 1535.87 -1.307 0.2276
## Week_13 1166.39 2410.31 0.484 0.6414
## Week_14 4030.56 3626.13 1.112 0.2986
## Week_15 193.04 2203.38 0.088 0.9323
## Week_16 1030.72 1381.93 0.746 0.4771
## Week_17 577.82 1513.72 0.382 0.7126
## Week_18 1907.75 1622.40 1.176 0.2734
## Week_19 513.95 1380.39 0.372 0.7193
## Week_20 -1281.64 1513.10 -0.847 0.4216
## Week_21 4363.44 1658.19 2.631 0.0301 *
## Week_22 41.49 1498.16 0.028 0.9786
## Week_23 -2198.68 1470.67 -1.495 0.1733
## Week_24 1860.18 1286.18 1.446 0.1861
## Week_25 966.42 1692.51 0.571 0.5837
## Week_26 -1731.03 1698.15 -1.019 0.3379
## Week_27 2733.47 2427.14 1.126 0.2927
## Week_28 -3773.68 1946.85 -1.938 0.0886 .
## Week_29 556.91 1977.39 0.282 0.7854
## Week_30 1876.28 1740.36 1.078 0.3124
## Week_31 369.58 1593.83 0.232 0.8225
## Week_32 -600.33 947.50 -0.634 0.5440
## Week_33 -2804.78 1769.86 -1.585 0.1517
## Week_34 2074.56 1819.28 1.140 0.2871
## Week_35 -2122.18 1250.01 -1.698 0.1280
## Week_36 3432.87 1678.73 2.045 0.0751 .
## Week_37 1239.02 2000.18 0.619 0.5528
## Week_38 -2025.65 1805.09 -1.122 0.2943
## Week_39 -790.84 1781.40 -0.444 0.6688
## Week_40 1590.43 1562.40 1.018 0.3385
## Week_41 -368.28 1838.55 -0.200 0.8462
## Week_42 451.98 1833.71 0.246 0.8115
## Week_43 -110.83 1431.54 -0.077 0.9402
## Week_44 -907.94 1065.41 -0.852 0.4189
## Week_45 -646.03 1592.99 -0.406 0.6957
## Week_46 -1443.39 1485.53 -0.972 0.3597
## Week_47 -904.31 905.25 -0.999 0.3471
## Week_48 1098.79 1556.88 0.706 0.5004
## Week_49 1208.57 818.25 1.477 0.1779
## Week_50 -1014.99 860.70 -1.179 0.2722
## Week_51 -2542.57 993.75 -2.559 0.0337 *
## Week_52 2863.56 1368.12 2.093 0.0697 .
## Week_53 -1253.87 715.14 -1.753 0.1176
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8321 on 8 degrees of freedom
## Multiple R-squared: 0.9006, Adjusted R-squared: 0.242
## F-statistic: 1.368 on 53 and 8 DF, p-value: 0.3366
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8816 -2698 765 2981 9094
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -43671.26 62465.98 -0.699 0.5043
## Week_1 102.83 1116.33 0.092 0.9289
## Week_2 91.01 1321.97 0.069 0.9468
## Week_3 977.08 1429.09 0.684 0.5135
## Week_4 642.01 1189.95 0.540 0.6042
## Week_5 -1503.25 1357.90 -1.107 0.3005
## Week_6 1684.53 1832.55 0.919 0.3849
## Week_7 663.88 1494.57 0.444 0.6687
## Week_8 -2254.98 2373.98 -0.950 0.3700
## Week_9 -233.27 1303.06 -0.179 0.8624
## Week_10 -4874.81 2068.33 -2.357 0.0462 *
## Week_11 -3311.42 3203.01 -1.034 0.3314
## Week_12 2091.01 2078.02 1.006 0.3438
## Week_13 586.76 3261.13 0.180 0.8617
## Week_14 -1237.21 4906.13 -0.252 0.8073
## Week_15 5846.04 2981.16 1.961 0.0855 .
## Week_16 1960.95 1869.74 1.049 0.3249
## Week_17 4846.62 2048.05 2.366 0.0455 *
## Week_18 -99.77 2195.10 -0.045 0.9649
## Week_19 2500.27 1867.66 1.339 0.2175
## Week_20 2429.33 2047.22 1.187 0.2694
## Week_21 -1966.57 2243.53 -0.877 0.4063
## Week_22 1595.38 2027.00 0.787 0.4539
## Week_23 -1397.62 1989.80 -0.702 0.5024
## Week_24 -3222.90 1740.20 -1.852 0.1012
## Week_25 -1082.16 2289.96 -0.473 0.6491
## Week_26 3451.49 2297.59 1.502 0.1714
## Week_27 1871.65 3283.91 0.570 0.5844
## Week_28 3016.32 2634.08 1.145 0.2853
## Week_29 -4239.79 2675.40 -1.585 0.1517
## Week_30 -730.59 2354.70 -0.310 0.7643
## Week_31 1496.45 2156.44 0.694 0.5074
## Week_32 -186.27 1281.96 -0.145 0.8881
## Week_33 -2601.00 2394.61 -1.086 0.3090
## Week_34 7501.91 2461.48 3.048 0.0159 *
## Week_35 71.91 1691.26 0.043 0.9671
## Week_36 -1000.53 2271.31 -0.441 0.6712
## Week_37 -2196.19 2706.24 -0.812 0.4405
## Week_38 2494.36 2442.28 1.021 0.3370
## Week_39 -5213.91 2410.22 -2.163 0.0625 .
## Week_40 3049.40 2113.92 1.443 0.1871
## Week_41 -4397.99 2487.55 -1.768 0.1150
## Week_42 1467.46 2480.99 0.591 0.5705
## Week_43 -1320.41 1936.86 -0.682 0.5147
## Week_44 -72.22 1441.49 -0.050 0.9613
## Week_45 -6995.59 2155.30 -3.246 0.0118 *
## Week_46 4763.70 2009.92 2.370 0.0452 *
## Week_47 429.47 1224.80 0.351 0.7349
## Week_48 -329.09 2106.45 -0.156 0.8797
## Week_49 128.17 1107.09 0.116 0.9107
## Week_50 -26.66 1164.52 -0.023 0.9823
## Week_51 -454.82 1344.54 -0.338 0.7439
## Week_52 2203.10 1851.06 1.190 0.2681
## Week_53 -1115.07 967.58 -1.152 0.2824
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 11260 on 8 degrees of freedom
## Multiple R-squared: 0.957, Adjusted R-squared: 0.6718
## F-statistic: 3.356 on 53 and 8 DF, p-value: 0.03649
## # A tibble: 2 × 3
## Crop_Type Start_Year End_Year
## <chr> <int> <int>
## 1 Barley 1991 2023
## 2 Canola 1991 2023
new crop data
